UNIQ+ projects

Supervisor

Dr Carolyn Nielsen

Description

The Draper group at the University of Oxford develop vaccines against the blood-stage of the Plasmodium falciparum and Plasmodium vivax parasites that cause the disease malaria. This includes running clinical trials to test leading vaccine candidates in both the UK and with collaborators in sub-Saharan Africa. The laboratory side of the clinical trials, including immunology assays to characterise vaccine-specific immune responses, is led by Ms Sarah Silk and Dr Carolyn Nielsen.

This project would be supervised by Carolyn and Sarah and be nested within the trial analysis taking place in July – August 2025. The aim will be to support improved understanding of antibody and B cell responses against the malaria vaccine antigens currently being tested. Specific project aims will be defined with the student ahead of time but could include comparison of responses between vaccine antigens, platforms, or age groups.

Outcomes

You will be trained in key clinical trial immunology assays for measuring vaccine-specific immune responses. We expect these to include ELISAs (for quantifying antibodies) and flow cytometry (for characterising B cell responses, the cellular source of antibodies).

You will also have the opportunity to gain first-hand exposure to how vaccine clinical trials are run in the clinic and laboratory, and be given the option of presenting your own data at an internal group meeting. If any aspect of your analysis is included in a future publication, you would be included as a named co-author on that paper.

Entry requirements

You should have, or be studying, a biology degree related to immunology and/or infectious disease. You should also have an aptitude for learning basic analysis skills and attention to detail to learn new lab techniques.

Funding information

Supervisor

Professor Matthew Higgins

Description

African trypanosomes are deadly pathogens which affect both humans and animals. We aim to understand how they use their surface receptors to help their survival. In particular, they live in blood and are attacked by the complement system. We are therefore using a combination of structural biology and biophysical methods to understand how.

Outcomes

You will gain an understanding of:

• how to conduct a research project;
• structural biology (x-ray crystallography and cryoEM);
• protein production and purification; and
• methods to study protein-protein interactions

Entry requirements

Biochemistry/Molecular Biology/ Chemistry/Medicine-related subjects

Funding information

Supervisor

Professor Stephan Uphoff

Description

Bacteria are extremely adaptable, which allows them to infect new hosts, evade immune defences, and survive antibiotic treatments. Under harmful conditions, bacteria activate stress responses and can acquire mutations that make them more stress resistant.

Research in the Uphoff lab aims at understanding the interplay between phenotypic responses and genetic adaptation to stress. We have pioneered single-molecule and single-cell microscopy techniques that allow us to trace bacterial adaptation across enormous spatial and temporal scales, from cell populations down to individual molecular events.

Stress responses and tolerance mechanisms are particularly important for bacteria during infection. Phagocytic immune cells kill invading bacteria via a burst of reactive oxygen species that is thought to cause DNA damage. However, intracellular pathogens can withstand this damage and replicate within phagocytes. This project will utilise single-molecule imaging to visualize DNA repair functions in Salmonella enterica serovar Typhimurium bacteria after invasion of phagocytes.

Outcomes

You will gain hands-on skills in cutting-edge single-molecule fluorescence microscopy, culturing bacteria and immune cells, performing infection assays, and analysing your research data using various computer algorithms and software tools. You will be working alongside other lab members and have opportunities to learn about a range of different research projects and methodologies in the field of molecular microbiology.

You will join weekly lab meetings and present your findings at the end of the internship. If any aspect of your work is included in a future publication, you may be included as a named co-author on that paper.

Entry requirements

You should have or be studying a science degree. Our research is interdisciplinary, and we welcome students from a range of backgrounds, including biology, biochemistry, physics, computer science with an interest in addressing biological questions.

Funding information

Supervisor

Professor Lindsay Baker

Description

Single particle electron cryo-microscopy is a Noble Prize-winning imaging technique used to determine the atomic structure of proteins and understand how they assemble, function and interact with the cellular environment or pharmaceuticals. With recent advancements in technology, it is now possible to determine the structure of a protein in as little a few hours to days. However, the time required is highly dependent on the automatic particle picking software scientists use.

At Diamond Light Source, we have developed an automatic on-the-fly processing pipeline which allows users to go from sample to preliminary structure within a few hours. Currently, this only works for globular proteins. In this project, the student will be using machine learning and AI methods to optimise the particle picking algorithms to detect icosahedral and helical viruses. Successful execution of this project will greatly increase the speed in which scientists can solve the structure of medically important viruses.

Outcomes

The student will learn the basic theory and general workflow of protein structure determination using single particle cryoEM. They will actively contribute to optimisation of particle picking algorithms for detecting particles in cryoEM images using ML and AI software. They will learn how to validate ML or AI generated picking models. If validation is successful, the student will learn how to integrate the model into existing automatic data processing pipelines and distribute jobs on high performance computing clusters.

Entry requirements

You should have, or be studying for, either a biochemistry or computer science-related degree. You should have interest in compute-based research projects and a basic knowledge of Linux environment and simple bash commands. Experience in image processing is beneficial but not essential.

Funding information

Supervisor

Professor Francesco Licausi

Description

We combine biological modules 'borrowed' from different kingdoms to engineer new signalling pathways in plants. We want to use such novel pathways to elicit timely adaptive responses to environmental adverse conditions with the ultimate goal to boost crop resilience and productivity. We use cell and molecular biology techniques including GoldenBraid cloning, protoplasting, confocal microscopy and gene and protein expression analyses (realtime qPCR and western blotting). In the past, we engineered blue-light transcriptional switches for chloroplasts and animal-inspired hypoxia responsive modules.

Outcomes

The intern will learn to engineer proteins to perform specific tasks. They will also design constructs to express such proteins. We will measure outputs such as luminescence, fluorescence using confocal microscopy, and the production of specific metabolites. Depending on the projects, the intern will learn to grow plants in soil and in sterile conditions for transient or stable transformation.

Entry requirements

Applicants should be studying towards, or have completed a degree, biology or biological sciences. The candidate should have good knowledge about molecular biology of the cell.

Supervisor

Dr Christoph Treiber

Description

This project will look at how mobile DNA segments, called transposons, affect genes involved in controlling circadian rhythms. You will use fruit flies to investigate where in the genome transposons are inserted and how these insertions change host genes. You will have the opportunity to combine molecular biology techniques such as quantitative RT-PCR and single-animal genotyping with behavioural testing of flies.

In addition, you will be able to build on existing, unpublished high-throughput single-cell transcriptomic data and use this valuable data to identify novel candidate transposon-gene pairs that might contribute to behavioural variation between individuals.

Your work will aim to further our understanding how genomic variations within a population contribute to behavioural diversity.

Outcomes

You will have the opportunity to learn the molecular strategies we employ to investigate variations in the genomes of individuals and you will be trained to perform behavioural testing of fruit flies. In addition, you will be able to gain an insight on a transformative new technology, high-throughput single-cell transcriptomics, which we pioneered in the fly brain.

Entry requirements

You should be interested in understanding how our brains function and be motivated to learn wet-lab techniques as well as some light-touch computational analyses. Applicants must be studying towards, or have completed, a degree in molecular and cellular biology, genomics, and/or genetics.

Supervisor

Dr Joseph Poore

Description

180 billion litres of beer are drunk every year globally. This requires nearly 50 million hectares of farmland to produce the barley and hops that go into it; an area of land the size of Spain. The production of beer creates over 100 million tonnes of greenhouse gas emissions, and this has to be reduced in order to limit warming to 1.5 degrees.

What are the most sustainable ways to produce barley, hops, and beer? Can the impacts be reduced enough to limit global warming to 1.5 degrees? Some research has found that beer can be carbon negative if regenerative farming practices are used to remove more CO2 from the air than is emitted; are their claims true? Does that mean we should consume more?

The purpose of this internship is to upload agri-environmental data to the HESTIA platform, focusing on barley in the major global producing countries (Russia, Australia, France, UK, and Ireland) and also on hops. The data will come from published peer reviewed studies and also from the partner organisations who we work with. You will also work with data from breweries describing the production of beer. HESTIA will automatically calculate the life-cycle environmental impacts for different products. Your work would support our collaboration with The Waste and Resources Action Plan (WRAP), funded by the Department for Environment, Food & Rural Affairs (Defra). The day-to-day work would involve sourcing and reading studies, extracting inventory data, uploading these data to HESTIA, and then exploring and analysing the results.

Outcomes

You will work with our team to create new assessments of the environmental impacts of barley and beer in different countries under different production systems.

You will gain knowledge of: crop production systems, how to quantify agricultural sustainability (in particular using Life Cycle Assessment), and how to conduct literature reviews. You will gain particular skills in: Excel, Git, and also knowledge of working with JSON schemas.

You do not need prior skills in these areas and will have opportunities to learn on the job. A basic understanding of these skills would however offer you a faster start. You will also have the opportunity to work with a range of researchers from our team, including environmental scientists and software developers.

Entry requirements

We are open to applicants who are studying for degrees in any area.

Supervisor

Professor Rob Salguero-Gomez

Description

Grasslands cover approximately 40% of the Earth’s land surface and are crucial for global biodiversity, carbon storage, and ecosystem services. However, they face threats from climate change, land use changes, and biodiversity loss, challenging their resilience and sustainability.

This project proposes the use of AI-driven analytical pipelines in combination with hyperspectral cameras mounted on drones to monitor grassland resilience in Wytham Woods, Oxford. Hyperspectral imaging, with its ability to capture detailed spectral data across numerous wavelengths, will enable precise assessment of vegetation health, species composition, and stress responses in grassland habitats. AI algorithms will process and analyse the high-dimensional data, identifying trends and resilience patterns in response to environmental pressures.

This innovative approach will provide a scalable, non-invasive method for real-time monitoring, helping to establish early warning systems and inform conservation strategies. The insights gained could offer a model for grassland monitoring and conservation globally, advancing sustainable management practices.

Outcomes

As an intern on this project, you will gain hands-on experience in remote sensing, AI, and environmental monitoring. You will be trained to operate drones equipped with hyperspectral cameras, gathering high-resolution data across multiple spectral bands. Using specialized software, you’ll learn to process and analyse hyperspectral data, applying AI models to detect patterns in vegetation health, biodiversity, and stress indicators within grassland ecosystems.

This role will also involve training in statistical methods for ecological data analysis and resilience assessment, with guidance on selecting and implementing appropriate models. You’ll participate in team meetings, contributing insights and collaborating on findings with researchers. At the project’s conclusion, you will present your results to the group. Depending on the findings and the progress on the project, you may have the opportunity to co-author a publication including your analysis. This internship will equip you with valuable skills in ecological monitoring and advanced data science, applicable to diverse fields in conservation and AI-driven research.

Entry requirements

You should be studying, or have completed, a degree in environmental science, ecology, remote sensing, data science, computer science, or a related field. Proficiency in data analysis software and programming languages (eg Python, R) is essential, as you will work with hyperspectral data and AI models. Familiarity with machine learning techniques and libraries (eg scikit-learn, TensorFlow) would be advantageous, as would experience with geospatial data tools (such as QGIS or ArcGIS) or drone operation. A background in ecology or environmental monitoring is desirable, particularly with a focus on plant health and biodiversity. Strong analytical skills, attention to detail, and the ability to interpret complex data are essential. You should be a proactive learner, able to work independently and as part of a team. Effective communication skills are also valuable, as you will present findings and contribute insights to the research group.

Supervisor

Professor E.J. Milner-Gulland

Description

Working with WWF-UK, a team of researchers is developing a new Earth Tracker tool, to be launched at UNFCCC in Belem in late 2025. This will aggregate existing tools and frameworks to track whether countries are meeting the commitments that they made under the 2022 Global Biodiversity Framework, whether these commitments are enough to "bend the curve" for biodiversity, and which conservation actions should be a priority for each country.

In this project you will compile existing tracking initiatives, and carry out exploratory research to explore their fitness for purpose. You will analyse how the actions and countries covered by existing databases map to various sustainability goals, what components of biodiversity are covered, and where there are gaps. For example you may find that there is a lot of international interest in Protected Area coverage but very little on sustainable wildlife use, and maybe that conservation in tropical countries is well explored, but not in East and Central Asia. Your project will therefore highlight gaps in evidence about country-level action towards the Global Biodiversity Framework and ways that these gaps could be filled.

Outcomes

You will be part of a team working with a major conservation organisation towards an exciting new tool that could be influential in global conservation. You will learn about international biodiversity conservation policy, and you will also learn how to interrogate policy documents, and how researchers currently track progress towards international biodiversity goals.

Entry requirements

No specific skills required, just an interest in international conservation policy. Must be studying towards (or have studied) in the areas of environmental science or data science.

Supervisor

Professor Gail Preston

Description

Plant-associated microorganisms often face the challenge of colonising hydrophobic plant surfaces. They achieve this by synthesising chemicals known as biosurfactants that reduce surface tension and act as wetting agents. Similarly, agrochemicals such as fungicides or insecticides are often mixed with surfactants to enhance their effectiveness when applied to crops. However, surfactants not only help microorganisms to colonise plant tissues – they also interact directly with biological membranes and can disrupt membrane integrity.

This project will use microbiological techniques, microscopy and gene expression assays to examine the effect of surfactants on the viability, growth and virulence of plant pathogenic bacteria. The project builds on a current collaboration between the Preston group and Dr Luke Clifton at ISIS Neutron and Muon Source studying membrane-surfactant interactions, so you will also gain insight into the use of neutron reflectometry techniques to analyse membrane properties.

Outcomes

You will be trained in microbiological, microscopy and imaging techniques used to study bacterial growth and gene expression. You will have the opportunity to learn about how we can use neutrons to study membrane properties and to visit ISIS Neutron and Muon Source to learn more about how these experiments are performed. You will be encouraged to actively contribute to experimental design, data analysis and data interpretation and participate fully in lab meetings and group activities.

It is possible that the project could coincide with a period during which the group will be moving into the new Life and Mind Building, in which case the project will focus more on bioinformatics and data analysis to minimise disruption.

Entry requirements

You should have or be studying a science-related degree subject. An interest in microbiology, biochemistry and/or plant science will be advantageous. You should be willing and able to work responsibly with microorganisms in a laboratory setting with care, precision and attention to detail.

Supervisor

Dr Berta Verd

Description

Lake Malawi cichlids are an extremely diverse group of >850 species of freshwater fishes which have diverged from a single common ancestor over the last 800k years. Despite their rapid diversification, species are more closely related than human populations. We have generated inter-species hybrids, in both parental directions, of a riverine insectivore, (Astatotilapia calliptera) and an algae-grazing rock-dweller (Maylandia zebra). The two species differ in their behaviour and in their morphology: however, we are yet to quantify many of the differences between these two species and of their respective hybrid offspring.

You will be responsible for phenotyping anatomical (such as jawbone shape) traits in these species and their respective hybrid offspring from micro-CT scan data we have previously generated. From this shape analysis, you will determine whether the phenotypes are sufficiently different to pursue for quantitative trait locus (QTL) analysis, a technique which allows the association of genomic regions with a phenotype of interest.

Outcomes

You will be trained in the segmentation of micro-CT scan data, as well as the tools necessary to landmark the 3D models generated from these data to analyse bone shape. Additional training will be provided for statistical analysis of the shape data in R, which will be essential in determining the distribution of phenotypes in the hybrids relative to the founding populations. Dependent upon your interests, you will also have the opportunity to observe and contribute to behavioural experiments utilising the hybrids and consider the impact of parental inheritance on behaviour.

At the end of the project, you will have phenotyped a number of anatomical or behavioural phenotypes that will be taken forward for quantitative trait locus (QTL) analysis to determine the genomic basis of these phenotypes. If any aspect of your analysis is included in a future publication, you may be included as a named co-author on that paper.

Entry requirements

You should have, or be studying, a biological sciences related degree (broadly interpreted) or have a strong statistical background (which could include non-biologists). Familiarity with R would be preferred but is not essential. Ability to work independently is essential.

Supervisor

Professor Michael Bonsall

Description

Observational time series can be generated by many different underlying mechanisms particularly in earth systems such as how species interact in ecosystems. Unravelling this complex dynamical interaction between species from time series requires unique and novel approaches to statistical inference.

This project will focus on the use of both supervised and unsupervised machine learning approaches to make statistical inference on multispecies ecological time series. The aim will be to combine the use of AI/ML approaches to learn aspects of any/some (but not all) of the mechanisms underpinning interactions in a multi-species time series – these mechanisms might, for example, be the way in which predators interact prey with prey or how one species competes with a second species. This AI/ML approach will be embedded within mathematical models relevant to the underlying ecology to understand (and forecast) the dynamical interaction between species.

Outcomes

Through this project, you will have the opportunity to gain experience in a research project focused on statistical modelling of multi-species ecological time series. You will again experience of presenting, collating and writing the results. It is also anticipated that your results from this work will contribute to our research and we anticipate that the analysis will be included in a collaborative future publication.

Entry requirements

An interest in earth systems particularly ecology and dynamical systems. Some familiarity with statistical modelling, differential equations and machine learning would be advantageous. studying (or studied) Biology or Maths/Statistics to degree level.

Supervisor

Dr Laura Moody

Description

One of the most transformative events in history was the colonization of land by plants approximately 470 million years ago. 3-dimensional (3D) growth is an invariable and fundamental feature of all land plants, and the diverse morphologies exhibited across the globe are a result of the differential regulation of 3D growth processes.

This project will investigate the role of HECATE-like genes in 3D growth in the model plant Physcomitrium patens. Experimental work will include quantitative RT-PCR to determine whether these genes are induced by auxin and/or cytokinin, construct preparation, western blotting, and confocal microscopy to determine the subcellular localization of the proteins. The project will be supervised by both Laura Moody (group leader) and Zoe Weeks (postdoc).

Outcomes

You will build on a fundamental understanding of the genetic network that underpins the transition from 2-dimensional to 3D growth in plants. Primarily, you will determine the expression patterns of both the HECATE genes and the proteins they encode. You will also determine whether these genes and proteins are regulated by auxin and/or cytokinin. You will be trained in molecular techniques as well as confocal microscopy and will have the opportunity to contribute to other experiments ongoing in the lab.

At the end of the project, you will present at one of our lab meetings, and any results you obtain will be acknowledged by adding your name as co-author on any resulting publications.

Entry requirements

You should have, or be studying, a biology degree with an interest in plant developmental biology. Training will be provided, but you should be enthusiastic about learning new skills and developing the ability to work independently (with guidance always nearby).

Supervisor

Dr Ronelle Roth

Description

Arbuscular mycorrhizas (AM) are among the most important fungal groups in terrestrial ecosystems due to their ancient and widespread symbiotic relationships with land plants, including most crops. AM symbiosis enhances crop productivity by improving plant nutrition and increasing tolerance to biotic and abiotic stresses. AM symbiosis is maintained through intricately coordinated signalling, mainly driven by or resulting from the initial exchange of signals between the symbiotic partners.

The aim of this project is to determine the role of small RNAs as inter-organismal signals in the interaction. Project 1 will investigate the expression of candidate genes that might be modulated through sRNAs while project 2 will analyse the effect of AM fungal colonisation in mutants unable to generate small RNAs. You will quantify AM fungal colonisation in wild-type and mutant roots using histology and light microscopy followed by qRT-PCR to study expression of candidate genes that might be modulated by sRNAs.

Outcomes

As a molecular cell biology lab we will train you in basic molecular biology techniques such as gel electrophoresis and PCR, including qRT-PCR to study gene expression of a marker genes to quantify arbuscular mycorrhizal symbiosis in AM fungal colonised roots. Results will be analysed by running statistical tests to determine the extent of mycorrhizal fungal colonisation over a time course.

You will also learn histology including trypan blue staining fungal colonised roots and light microscopy to quantify levels of colonisation which you will compare with molecular gene expression results. You will have an opportunity to present your findings at our weekly lab meetings and if your analysis is included in a future publication you will be included as a co-author.

Entry requirements

You should have a degree in plant molecular biology and ideally be familiar with R and statistical methods. Full training will be provided in molecular biology techniques used in our lab.

Supervisor

Dr Ricardo Rocha

Description

Brazilian beef is the most environmentally damaging food sector in the world. It is already responsible for 72% of Brazil’s deforestation and if current trends continue, this system could drive catastrophic ecological collapse, climate change and the emergence of zoonotic pathogens.

Bats play critical roles in human-modified ecosystems, providing numerous services to people, such as suppression of agricultural pests and consumption of pathogen-carrying arthropods. Bats exhibit considerable variation in their sensitivity to human disturbance.

While many species avoid humanized landscapes, numerous others benefit from human/livestock presence and can even be characterized as synanthropic. Furthermore, as human numbers increase and people encroach deeper on remaining natural habitats, human-bat interactions are becoming more frequent, with often undesirable consequences to both humans and bats (eg zoonotic disease spill over).

Using bioacoustic data collected in Brazil, this desk-based project will investigate changes in insectivorous bat assemblages in relation to livestock-induced habitat change in the Amazon and Cerrado biomes.

Outcomes

You will receive comprehensive training in bioacoustic analysis of bat echolocation calls, along with ecological analytical methods for assessing the impact of habitat change on biodiversity-rich animal communities. You’ll have the opportunity to participate in weekly meetings of the Interdisciplinary Centre for Conservation Science, where you can present your work and engage with other researchers. Additionally, if your contributions are included in a future publication, you may be credited as a co-author.

Entry requirements

You should have, or be pursuing, a degree in a biology-related field with a strong interest in ecology and conservation. Experience with R and ecological statistical analyses is beneficial.

Supervisor

Professor Lindsay Turnbull

Description

Coral bleaching surveys are essential for tracking the health of coral reef ecosystems through a bleaching event, by documenting the extent and severity of bleaching. Bleaching surveys typically involve recording coral colonies and the extent of their bleaching (eg healthy, partially bleached, fully bleached) within a specific area.

This project focuses on the corals at Aldabra Atoll, where multiple video surveys of corals on ten different reefs were conducted during the recent global bleaching event. Your role will be to observe and record the bleaching status of individual coral colonies in defined areas on the survey videos, and compile and provide preliminary summary analyses on the data. This will provide valuable bleaching survey data on multiple reef sites at Aldabra, and will go towards gaining a better understanding of the effects of a global bleaching event on remote reefs.

Outcomes

You will be trained in coral identification and coral bleaching assessments, and how to extract the relevant data from underwater video transect footage. You will gain valuable experience in coral reef surveying during a global bleaching event, and specifically will learn to determine species, size, growth morphology and bleaching status of coral colonies.

At the end of the project you will present your data summary together back to the group in an internal meeting. If any aspect of your analysis is included in a future publication, you may be included as a named co-author on that paper.

Entry requirements

You should have, or be studying, a biology related degree. Applicants with a strong background in image processing are also welcome to apply. In general, having an interest in marine biology, coral reefs and ecosystem resilience would be highly advantageous, and experience in coral species identification would be useful (but not required). Familiarity with image processing and R would also be potentially helpful.

Supervisor

Professor Renier van der Hoorn

Description

Molecular Pharming is a biosynthetic technique which uses a plant pathogen known as Agrobacteria, to infect and transfer genes into plants for protein production. This technique has great potential as a new way to produce proteins, as it is more sustainable, more scalable, and faster than current mainstream options which mostly rely on animal cells. Molecular Pharming has already been used to produce important medical and scientific products, such as vaccines for Covid-19, and antibodies used for diagnostics and research.

This promising platform is not without its problems: one of the biggest challenges is increasing product yield. In order to make Molecular Pharming more efficient, we must understand the interactions between the pathogen Agrobacteria, and its plant host's immune landscape. You will help identify and profile potential 'problem interactions' that may hinder the bacteria's infection process and reduce downstream protein production. By investigating these host-pathogen interactions, you will contribute to overcoming these obstacles and help enhance the efficiency of this new and exciting protein production platform.

Outcomes

You will have the opportunity to manage a self-contained research project typical in postgraduate degrees in Molecular Biology. Your main task will be to create and optimise a reporter Agrobacteria, which is a specially modified bacteria strain designed to monitor gene expression in plant tissues. You will design the strain to report the expression of a gene that Agrobacteria naturally expresses during infection to overcome plant immune responses. You will then use this reporter Agrobacteria to screen for changes in bacterial gene expression in response to the immune landscape of various plant species, and assess their impact on protein yield in Molecular Pharming.

You will be trained in a wide variety of essential molecular biology techniques, such as bacteriology, cloning, PCR, sequencing, gel electrophoresis, and Western Blots, as well as Molecular Pharming techniques, such as agroinfiltration and plant husbandry. You will gain extensive experience designing and managing both in-vitro and in-planta assays. You will learn to collect data using our imaging equipment, including the LAS4000, and the Amersham Typhoon, and analyse the data using tools such as R and ImageJ. You will be encouraged to join and present at our lab meetings, learning from our diverse team of lab members, researching a wide variety of topics across plant pathology.

At the end of the project, you will have successfully developed a reporter Agrobacteria ready for use in further research, and will present your findings at a lab meeting. If any of your work is included in future publications, you will be acknowledged and credited.

Entry requirements

You should have, or be studying for, a degree in Biology or any related subject. You should have an interest and basic knowledge in molecular biology. Any prior wet lab experience, as well as experience with the programming language R, would be useful, but not essential. You should be motivated, open minded, and capable of working both independently and collaboratively within the team.

Supervisor

Dr Thomas Hesselberg

Description

Wytham Woods, near Oxford, is one of the most studied woodlands in the world and is hosting a range of long-term studies on tits, badgers and bats. However, we know less of its invertebrate diversity, especially in the less accessible habitats. One particularly overlooked habitat in woodland biodiversity studies is the holes and crevices found in older trees, which can shelter bats and are home for a range of invertebrates including snails, woodlice, beetles and spiders.

In this project, we will expand the long-term study on bats in Wytham Woods by Dr Dani Linton to investigate how invertebrate biodiversity in tree crevices is influenced by variables relating to the crevice itself, the tree it is found in and the location of that tree within the woodland. An endoscope will be used to count and ID the invertebrates in the crevices and analyse our findings with advanced spatial and statistical techniques.

Outcomes

Firstly, You will gain skills in ecological surveying and species ID to measure tree characteristics (species, tree height, diameter at breast height and cavity size) and identify and count invertebrates inhabiting the tree cavities with an endoscope.

Secondly, you will gain skills in mapping the location of trees using GPS and QGIS software, and potentially using remote sensing data such as LIDAR. Thirdly, you will learn to analyse and visualise the data that you obtain during this project with the statistical programming software R.

Finally, you will present your data for the group and depending on the quality of the obtained data might be involved as author on a resulting scientific publication.

Entry requirements

You should be studying or have completed an ecology related degree and be prepared to spend long field days in Wytham Woods. Experience with identifying British terrestrial invertebrates and an aptitude for data analysis and GIS would be advantageous.

Supervisor

Dr Yingxi Zhao

Description

Medical degree apprenticeship, a new way of obtaining medical degrees, is set to launch in the UK this year, with proponents aiming to enhance access to medical careers and ensure graduates acquire skills directly aligned with workforce needs. However, concerns around equity, supervision, and the program’s effectiveness have been raised by some stakeholders.

This internship, building on work by the Health Systems Collaborative team on UK and global health workforce issues, will involve a series of literature and policy reviews as well as social media analytics to explore the historical context and current state of medical apprenticeships in the UK and internationally. Through this work, the intern will develop skills in conducting comprehensive literature and policy reviews or social media analytics and applying analytical frameworks and theories.

Outcomes

You will develop skills and understanding of literature reviews and/or social media analytics, including developing a search strategy and conducting thematic coding, and experience of working with an applied health research team.

We will expect you to produce a report or journal paper or other relevant output to disseminate the findings - and to present this to colleagues in the Health Systems Collaborative team.

Entry requirements

You should have, or be studying, a degree in medicine, allied health, social sciences (eg education or policy), but you are welcome to apply from any subject background.

Supervisor

Professor Richard White

Description

Cancer does not occur randomly in the body - some locations are more prone than others. Recent work from the White lab has uncovered why some skin cancers like melanoma occur in certain anatomic locations, but there is much still to learn. For example, we don't know how to target this "positional" effect for therapy.

In this project, we will use stem cell models of cancer to uncover mechanisms that determine why cells take on certain positions in the skin.

Outcomes

The student will learn stem cell culture, genetic manipulation and imaging.

Entry requirements

You should have some background in biology, biochemistry or genetics.

Funding information

Supervisor

Professor Chunxiao Song

Description

Cellular RNA is decorated with diverse chemical modifications, which participate in all aspects of RNA biology. The multitude of modifications in RNA adds a new layer to gene regulation, leading to the emerging field of epitranscriptomics. Our research aims to decode the chemical modifications of our genome, transcriptome, and proteome in human health and disease – cancer in particular – and translate this information into diagnostic and therapeutic opportunities that ultimately benefit patients.

Recently, we developed a novel sequencing method, called BACS, for the most abundant RNA modification pseudouridine (Nat. Methods 2024, 10.1038/s41592-024-02439-8). We are now studying the role of pseudouridine and pseudouridine synthases (PUS) in cancer, and exploring the potential clinical application.

Outcomes

To learn how to conduct and interpret biochemical experiments that will contribute to the groups' research.

Entry requirements

A Biology or Chemistry or a related science background would be required.

Funding information

Supervisor

Dr Robert Beagrie

Description

Cornelia de Lange Syndrome (CdLS) is a genetic disease that affects multiple organs including the brain, heart, limbs and gut. It is usually caused by mutations in NIPBL, a gene that controls the way DNA folds in the cell nucleus. In order to study the role of DNA folding in the development of different tissue systems, we use mice in which one copy of the Nipbl gene is knocked out.

We have generated high resolution 3D imaging datasets from mouse embryos carrying Nipbl mutations and control, wildtype embryos. In this project, the student would be trained in how to analyse these datasets and to identify the developmental issues that commonly affect CdLS patients (eg malrotation of the gut). This would allow us to pinpoint the affected organ systems and design future experiments to understand why those tissues are specifically affected by errors in DNA folding.

Outcomes

You will be trained in computational software used to analyse 3D imaging data, in how to measure the size and shape of various different organs of interest, and in which statistical tests to apply to identify significant differences between mutant and wild-type embryos. You will also have the opportunity to observe and potentially contribute to other molecular biology experiments going on in the lab during your stay.

At the end of the project you will present your findings back to the group in an internal meeting. If any aspect of your analysis is included in a future publication, you will be included as a named co-author on that paper.

Entry requirements

Applicants may have studied or be studying towards a degree in any academic discipline aligned with the project. All required training will be provided.

Funding information

Supervisor

Dr Azim Ansari

Description

Embark on an exciting scientific journey to unravel the mysteries of the Hepatitis C virus (HCV), a RNA virus affecting millions worldwide. This project will investigate chronic HCV infection, a leading cause of severe liver diseases such as cirrhosis and liver cancer.

Our mission is to explore how the virus adapts and thrives within the human body, driven by selective pressures from the host immune responses. By identifying key mutations, we can gain valuable insights into the complex interactions between the virus and its host, with far-reaching implications for developing cutting-edge therapies and vaccines.

Central to our research is the innovative Genome-to-Genome (G2G) analysis. This groundbreaking method connects human and viral genetic data, revealing hidden associations and uncovering previously unknown genes involved in infection processes. Recent technological advancements in sequencing and data analysis have opened up new possibilities for exploring these vast genomic landscapes.

In this project, you will work with extensive paired host-HCV datasets to pinpoint specific genetic variants influencing viral evolution. Join us in this pioneering research to make significant contributions to the field of viral genomics and transform our understanding of host-pathogen dynamics.

Outcomes

By participating in this project, you will gain a foundation in programming and learn to manage large-scale human genetic and viral sequencing data. You will learn genome-wide association analysis techniques and develop an understanding of genomics. This experience will equip you with valuable skills for future research and innovation in the field.

Entry requirements

You should have, or be studying, a degree in biology, statistics or relevant field. Previous programming experience in bash/Python/MATLAB/R/Java is desirable but not essential.

Funding information

Supervisor

Dr Attakrit Leckcivilize

Description

Text analysis using Machine Learning techniques have been used in various fields such as political science and economics. These text analysis tools can help to group 'text' by similarity, extract key themes from the articles, and explore writers’ sentiments. Despite the usage of these tools with eg patients’ records and feedbacks, they have not been employed to study health policy or public perception extensively.

This project aims to use text analysis tools to explore, extract and visualise key information from news articles of major news outlets in the UK regarding Physician Associates in the NHS. Physician associates (PAs) are healthcare professionals with a generalist healthcare education who work alongside doctors and surgeons providing medical care as an integral part of the multidisciplinary team.

However, there are concerns on issues such as patients safety, training, and integration into clinical teams. We expect the results from this project to be a proof of concept and feed into a further exploration on this topic across countries and international organisations.

Outcomes

You will have an opportunity to explore news articles with text analysis techniques, while learning more on the debates around health workforce in the UK. At the end of the project you will present the findings to the group. We also hope to publish the findings as research article(s) in peer-reviewed journal. And if possible, it will be used to support our team's future application for external funding to explore health workforce policy in the UK.

Entry requirements

Good knowledge in programming and Machine Learning is essential and interest in health care issues and policies would be advantageous.

Supervisor

Professor Frank von Delft

Description

Antimicrobial resistance (AMR) threatens the effective prevention and treatment of an ever-increasing range of infections caused by bacteria, parasites, viruses and fungi, also referred to as “superbugs”. The antimicrobial discovery and development community faces many challenges which hold back the advancement of life saving therapies, not least that biopharma considers the problem too difficult to invest into. We believe instead that what is lacking are protein targets that are researched thoroughly enough to permit accelerated rational drug discovery: proteins that enable targeting novel modes of action, along with suitable chemical matter that shows how to exploit them.

In this project you will establish a new target protein for direct-acting antimicrobials. The techniques you will employ includes target informatics, protein chemistry, high-throughput biochemistry and structural biology. The project aims include the design the DNA constructs that yield fit-for-purpose proteins, the production of high-quality reagent and the generation protein crystal structure that can feed into an AMR drug discovery program.

Outcomes

You will be trained to do hands-on laboratory experiments, including molecular cloning, protein production and protein crystallography, and the computational software used for informatics analysis and solving crystal structures. At the end of the project you will present your findings back to the group in an internal meeting and prepare a preprint on your findings to be submitted to the BioRxiv server.

Entry requirements

You should have a basic knowledge of molecular biology and biochemistry and be willing to spend most of your internship doing experiments in a wet lab. Ideally, you will also have an aptitude for computer-based analysis.

Funding information

Supervisor

Dr Makoto Saito

Description

Clinical care in poorer countries often lacks strong supporting evidence, even though infectious diseases are the leading cause of morbidity and mortality in many of these areas. As part of the Infectious Diseases Data Observatory (IDDO)’s aim of enabling evidence-based decision-making to combat infectious diseases, our current project uses systematic reviews of existing literature to gather evidence regarding the safety of antimalarial drugs during pregnancy, and antimicrobial resistance in low- and middle-income countries.

We have extensive experience of such work, and have streamlined the evidence-gathering process, with our work feeding in to the development of numerous clinical guidelines, including the World Health Organization’s malaria guidelines. We seek individuals interested in understanding these topics and the process of evidence synthesis. Expected activities include reviewing medical literature and summarizing findings by extracting relevant data. You may also have opportunities to contribute to report writing based on these findings.

Outcomes

Participants will gain a deeper understanding of the context (malaria or antimicrobial resistance) and develop skills in critically appraising published literature, an essential first step for many scientific projects, including defining a postgraduate project which clearly addresses a knowledge gap regardless of whether it involves wet lab or dry lab work.

Working in collaboration with our team, participants will also gain an overview of how to conduct a proper systematic literature review and synthesise existing evidence.

Entry requirements

Applicants must be studying towards, or have completed, a degree in Medicine or Medical Science to be eligible for this project. Applicants should have a basic understanding of medical terminology and be competent in reading medical articles. No prior experience in statistical analyses or data management is required, although it can be helpful.

Funding information

Supervisor

Professor Esther Becker

Description

The spinocerebellar ataxias (SCAs) are a complex group of inherited neurodegenerative disorders that are characterized by the dysfunction of the cerebellum. Patients affected by SCA have difficulty with walking and balance, fine motor skills, speech and swallowing, as well as eye movements. SCAs are debilitating diseases and can lead to an early death. No effective treatments currently exist for patients and there is thus an urgent need to develop new therapeutic strategies.

This project will focus on the molecular and cellular mechanisms that cause neuronal dysfunction and degeneration in SCAs. Our lab has previously identified aberrant mGluR1 signalling as a key driver of disease. The project will further advance our understanding of the underlying mechanisms and how these could be utilised to develop treatments. The project will involve molecular biology techniques, Western blotting and immunofluorescence microscopy.

Outcomes

You will gain experience in experimental design, molecular and cellular techniques, and data analysis. Overall, the project will help us to understand how abnormal mGluR1 signalling causes disease and how this pathway could be targeted therapeutically. You will present your work at our lab meeting and also produce a short report about your project.

Entry requirements

The project is suitable for students from a life sciences/biology/biochemistry/pharmacology or related background.

Funding information

Supervisor

Dr Alexander Davies

Description

Our lab investigates how the immune system modulates pain in the body. In childhood neuroblastoma, a nerve cell cancer, a common treatment involves an immunotherapy containing an ‘anti-GD2' antibody that targets and destroys cancer cells but also causes nerve pain. We aim to understand how this antibody causes pain.

To do this, we will:

1. identify where in body the antibody targets nerves in animal models of neuroblastoma, using in vivo imaging and tissue immunohistochemistry; and
2. analyse immune cell profiles in both neuroblastoma patients and animal models undergoing anti-GD2 antibody treatment, through flow and mass cytometry.

We have engineered a variety of therapeutic anti-GD2 antibodies intended to reduce pain while preserving their anti-cancer effectiveness. We are currently testing these engineered variants by conducting sensory and motor behavioural analyses and immune profiling in a neuroblastoma mouse model after administering the modified antibodies to determine whether they meet these goals.

Outcomes

We will help you identify areas to pursue in your future career by involving you in an interdisciplinary project, where you can gain foundational knowledge in immunology, neuroscience, and immunotherapy.

You will also gain hands-on experience with techniques such as cell culture and immunohistochemistry, essential for careers in biomedical research and diagnostic laboratories. Additionally, you may participate in the analysis of mouse sensory-motor behavioural tests, which will provide valuable experience for preclinical and scientific careers.

As well as weekly supervisory meetings, you will take part in regular meetings of the Neural Injury group, where you will learn from a range of experts (>35 researchers including postdocs, clinicians, DPhil students, technicians and clinical support staff) in the field of peripheral neuropathies and neuropathic pain. You will have the opportunity to present your final report to the Neural Injury group, and any analysis you produce for the project that is included in a scientific publication would be acknowledged by co-authorship.

Entry requirements

You will have studied (or be studying) a biomedical science or related degree, and be familiar with basic lab bench techniques including sterile technique, pipetting and liquid handling. You will also have a strong understanding of the core biological processes underlying neuronal and immune cell function, the anatomy of the somatosensory nervous system, and the principals of immunohistochemistry and fluorescence microscopy.

Funding information

Supervisor

Dr James Grist

Description

This project will focus on developing a computer simulation that can be used to describe, and more importantly optimise, metabolic imaging experiments in humans. You'll use data already present in the lab, as well as fundamental physics mathematics, to make this framework as true to real life as possible. You'll use Python or Matlab to code the project and be well-supported in your time here.

Outcomes

You will be trained in fundamental MRI physics, python, Matlab, and image processing. You will have the opportunity to engage in lab meetings and experience and understand the work being performed by other members of the lab. We'll involve you in research discussions and the day to day life of the lab, we love to have new members come and join us! You'll be able to present your work at lab meetings and gain experience in scientific presentation.

If completed, you'll be able to publish this work.

Entry requirements

Experience in use of Matlab or Python is required, background in engineering and /or physics and / or computer science. You'll be the right person if you enjoy working with others but on a specific project.

Funding information

Supervisor

Professor Qiang Zhang

Description

AI deep learning is transforming the world in many aspects, but its real-world clinical applications have been hindered by the knowledge gap between machine learning scientists and clinicians. We actively address this by developing AI algorithms next to clinical doctors at an interdisciplinary clinical research unit. We offer opportunities to work with a cross-disciplinary team to gain experience in developing deep-learning solutions for unmet clinical needs. This may include data pre-processing, neural network design, data analysis, and method validation.

You will have the chance to observe real-world clinical MR scans at the Division of Cardiovascular Medicine, and access to computing facilitates at Oxford Big Data Institute.

Outcomes

You will gain domain knowledge of both deep learning and cardiovascular imaging, skills in medical data processing, neural network design in Python, and valuable experience in developing AI algorithms in clinical research settings.

Entry requirements

You should have a background in computer science or engineering. You should have experience in machine learning and coding in Python.

Funding information

Supervisor

Professor Ellie Tzima

Description

Our arteries are exposed to various types of blood flow depending on their shape. When blood flow is turbulent, endothelial cells that line arteries become inflamed and activated, resulting in chronic inflammation and development of plaques. These plaques can obstruct blood flow to the heart or brain and cause heart attacks or strokes. The mechanisms by which endothelial cells sense and respond to turbulent blood flow are a mystery.

Work from our group has identified specialised receptors expressed on the surface of cells whose function is to detect blood flow and send signals that ultimately result in disease. One of these receptors is called Plexin D1. We now aim to understand in greater detail the mechanism by which Plexin D1 senses blood flow and how it signals to other cells to form a plaque.

Outcomes

The project involves a combination of tissue culture cell-based experiments, molecular biology, and advanced microscopy techniques. The project has the potential of being tailored to suit your research interests and techniques you want to specialize in.

Entry requirements

You should be studying for a Biochem/Biology/Biomedical Sciences degree or Medicine.

Funding information

Supervisor

Professor David Sims

Description

Data visualisation is an integral part of biomedical data science, critical to the exploration and interpretation of experimental data. We have developed an R/Bioconductor package called iSEE for the interactive visualisation of virtually any biomedical assay, including large genomic and proteomic datasets. This project aims to build the functionality of the iSEE universe. This may include the development of new interactive visualisations methods, new functionality improving user experience, and demonstration workflows for a range of biomedical assays, such as single-cell RNAseq.

Outcomes

You will be trained in the R programming language and the use of Bioconductor packages to analyse a wide range of biomedical data sets. You will learn about software development best practices including version control (Git) and testing using continuous integration. You will gain experience in the design of an interactive graphical user interfaces, and in writing and publishing accompanying online documentation.

At the end of the project you will present your contributions to the group in an internal meeting. Your contributions will be recognised as a named contributor in the documentation of all the relevant software packages.

Entry requirements

You should have, of be studying, a degree related to either computer science or biomedical data science and have some experience of programming at an undergraduate level. Familiarity with R, bioinformatics libraries, and JavaScript would be useful. If you have an interest in web technologies or cloud computing, it would be advantageous.

Funding information

Supervisor

Dr Joseph Clarke

Description

One mechanism by which tumours can evade the immune system is by inhibition of killer T cells, which would otherwise carry out cytotoxic effector functions to kill tumour cells. One way tumour cells do this is by engaging inhibitory receptors on the surface of the T cell. Once these receptors are engaged, a key signalling molecule, SHP-2, is thought to be critical in establishing T cell inhibition. Therefore, targeting of the SHP-2 molecule may provide one way of releasing T cell inhibition.

However, targeting both SHP-2 and other molecules known to mediate inhibition may be beneficial in reversing T cell inhibition during the anti-tumour response. This project aims to address whether targeting SHP-2 alongside a list of other proteins, known to interact with SHP-2, can lead to better T cell responses against tumours. To do this, the student will utilise techniques such as cell culture, molecular cloning, lentiviral transductions as well learning how to perform functional T cell experiments measured using flow cytometry.

Outcomes

You will have the opportunity to learn key wet laboratory techniques such as tissue culture, molecular cloning and lentiviral transduction, as well as functional T cell assays and flow cytometry. Additionally, this project will use CRISPR-Cas9 technologies to target genes of interest (ie PTPN11, the gene which encodes for SHP-2), and will therefore provide a basic insight into how CRISPR-Cas9 gene editing is performing.

This project will provide basic training in the described techniques, as well as provide understanding of the textbook theories behind T cell activation and inhibition, in the context of anti-tumour responses. You will learn how to analyse the functional data you acquire from flow cytometry based experimental readouts, and will have the opportunity to present some of this data at regular lab meetings as well as presenting your collected findings to the group before you leave. Finally, there will be scope to get involved with other on-going projects within the lab.

Entry requirements

You should have, or be studying, a biological science related degree and have a basic understanding of how T cells work at an undergraduate level, and a keen interest in Immunology as a whole would be ideal. Previous laboratory experience would be useful.

Funding information

Supervisor

Dr Karina Pombo-Garcia

Description

Our gut ages, which has implications for the cellular organization of proteins involved in cell-cell adhesion. Cell-cell adhesions are like the building blocks of a house, and the proteins responsible for holding them together act as the glue that allows our organs to function. In this project, you will have the opportunity to visualize, at very high resolution (on the nanometer scale), the distribution and organization of cell adhesion proteins in a gut-like model called gut-organoids. We will use patient-derived organoids from individuals of different ages to map how these proteins assemble as we age.

You will learn and use super-resolution microscopy with fluorescence proteins to visualize them in human tissue. Additionally, you will get familiar with handling the organoids and observing how they phenotypically change over several days in culture. While not required, it would be ideal if you have some basic knowledge of coding, such as Python, to assist in processing the images.

Outcomes

You will gain experience in several key cell biology techniques as well as being immersed in an active research environment. This will enable broadening of expertise, as well as help you derive a better understanding of studying and working in a research laboratory.

The project itself will allow for training in cell culture and aseptic techniques. You will also be trained on key super-resolution imaging microscopy STED , as well as gut organoid development and maintenance.

There will also be the opportunity to work in a lab with a range of experience from junior to senior scientists who are willing to advise and mentor. If successful, the data and resources generated will have a real-world impact on ongoing research with you contribution credited accordingly if work with their direct involvement is published.

Entry requirements

Applicants must be studying toward, or have complete, a degree in biology, biochemistry, or medicine. It would be ideal if you have some basics of cell biology and microscopy but not required and some familiarity with python. The most important skills are motivation and curiosity for science.

Funding information

Supervisor

Dr Sumana Sharma

Description

Gamma delta (γδ) T cells are a unique subset of T cells characterized by their distinct T-cell receptor (TCR) composed of γ and δ chains, differing from the conventional alpha beta (αβ) T cells. Engineering gamma delta (γδ) T cells presents a promising approach in immunotherapy due to their unique ability to recognize stressed or malignant cells without MHC restriction. We have established techniques to engineer (αβ) T cells through over-expression and knockout approaches, which we have started to translate to (γδ) T cells.

Outcomes

You will be assisting with these ongoing efforts by learning to culture primary T cells, editing primary T cells, and performing various cellular assays to characterise the function of these engineered cells. At the end of your project, you will have the opportunity to present your work to the members of the lab and gain feedback.

Entry requirements

You should have, or be studying, a degree in molecular biology, biochemistry, biophysics, or biological sciences.

Funding information

Supervisor

Dr Monica Olcina

Description

Paediatric high-grade gliomas (pHGGs) are malignant, deadly tumours developing in infants and children. pHGGs are fast-growing and diffusive which makes them hard to remove or treat. For some of these tumours radiotherapy remains the only option with transient benefits. Unfortunately, most children only survive for 9-15 months from the time of diagnosis. We are interested in understanding how interactions between tumour cells and host immune cells in the tumour microenvironment (TME) drive resistance to treatment.

The aim of the project is to use blockers of tumour-host interactions to improve radiotherapy and potential future novel immunotherapy treatments. Techniques used to address this aim may include assessment of gene and protein expression by standard molecular biology and microscopy techniques. The effect of drugs on tumour cell survival will be assessed in cell cultures. Analysis of stained tumour or normal tissues may also be undertaken.

Outcomes

You will have the opportunity to gain experience in shadowing and undertaking experiments to assess gene and protein expression changes in tumour and immune cells under different treatments. You will also learn how to assess the effect of treatments on tumour cell survival.

Entry requirements

You should have, or be studying, a biological science of biomedicine related degree. Familiarity with coding (Python or R) would be useful but not essential.

Funding information

Supervisor

Professor Mark Coles

Description

At the Kennedy Institute we aim to understand mechanisms leading to chronic non-resolving inflammation and identify pathways that can lead to resolution of inflammation. To understand the cellular and molecular mechanisms underpinning chronic inflammation we have been using multiplex (20-60 antibodies) imaging on tissue sections from needle biopsies to quantify cellular microenvironments in both normal and chronically inflamed tissues.

In this project you will be involved in undertaking imaging of paired biopsies and applying image analysis pipelines to quantify cellular neighbourhoods focusing on the co-localisation of immune cells and specialised fibroblasts. Specifically, we aim to quantify cellular neighbourhoods associated with barrier membranes in health and chronic inflammatory disease.

Outcomes

You will be trained on using state-of-the art multiplex imaging systems to analyse human tissue biopsies from patients with rheumatological disease. You will learn skills in sample processing, imaging and analysis, including topological analysis. You will have the opportunity to observe and contribute to functional assays in the lab during your stay.

At the end of the project you will present your findings in a short presentation to the lab group. If your analysis is used in future publications you may be included as a named co-author on that publication.

Entry requirements

A background in the biological science or interest in image analysis (computer science, physics, mathematics). Some experience with python is useful but not necessary, depending on student background and interest the project can be modified to either focus on biological samples or on image analysis (requires experience with python).

Funding information

Supervisor

Dr Marti Catala Sabate

Description

Join a dynamic and multidisciplinary team in the Health Data Sciences group. Our team includes experts from fields such as medicine, pharmacy, mathematics/statistics, working together to leverage real-world data (RWD) from hospitals, general practices, and disease registries to improve public health.

While essential for testing new treatments, clinical trials are conducted in controlled settings with carefully selected patient groups. This limits their ability to fully represent how treatments perform in the real world. By contrast, RWD reflects the broader population and real healthcare practices, offering insights that clinical trials might miss—such as unobserved side effects or how treatments are used in routine care. However, since RWD was not originally collected for research, careful processing and analysis are required to ensure reliable scientific evidence.

In this internship, you will reproduce and characterise a population from a clinical trial using RWD and use it to answer relevant clinical research questions.

Outcomes

This internship provides comprehensive training in R programming, big data handling, clinical epidemiology, and biostatistics. You’ll have the opportunity to build your presentation skills by regularly presenting your work in team meetings, with potential for co-authorship on project publications. These skills are highly valued in both academia and industry, providing a solid foundation for future job applications and career development.

Entry requirements

Applicants should be studying a STEM subject, and familiarity with the R programming language is desirable.

Funding information

Supervisor

Dr Annika Jödicke

Description

Understanding how well new medicines for cardiovascular and metabolic disease work, and how safe they are in real-world settings is essential. This project will focus on “real-world evidence” (RWE), referring to studies using data gathered in routine care settings, such as by general practitioners in primary care, or in specialist settings of hospitals.

Systematic reviews of the literature provide a comprehensive overview of the published knowledge at a time. This is particularly important to inform future research.

Students will begin by developing a protocol for a literature review, including a search strategy and criteria for including or excluding studies. With guidance from supervisors, students will then review and discuss the identified studies, and write a summary of the findings. This work will provide valuable experience in research methodology, with the potential to be published as part of a project report or scientific manuscript.

Outcomes

You will have the opportunity to gain experience in conducting literature reviews using a systematic search strategy. We will support you in developing a protocol for the review, work with specialists at the Bodleian Libraries to develop a search strategy, teach you how to screen titles and abstract, and extract relevant information from the scientific publications we shortlist.

We will aim to write a report on the literature review that will be published alongside the protocol, and (where possible) include the findings from the literature review for the introduction/discussion sections of future research publications or project reports.

Entry requirements

The project will be best suited for people with an undergraduate degree in medical-related fields, eg public health, nursing, pharmacy or medicine, or statistics/epidemiology. Applicants ideally have an interest in reading medical literature and are interested in learning how to conduct literature reviews.

Funding information

Supervisor

Dr Sofia Massa

Description

The aim of the project is to gain a deeper understanding of the methods and techniques used to analyse health data coming from randomised controlled trials. You will be part of our group of statisticians that will be able to share their knowledge and enthusiasm using statistics to address important clinical questions for the benefit of patients.

You will be able to work with real and simulated datasets to compare the common used methods to analyse the typical types of outcomes encountered in these studies. Depending on your interests different avenues of research will be possible.

Outcomes

You will receive specialised training in the analysis and interpretation of health data and randomised controlled trials data. If any aspect of your analysis is included in a future publication, you may be included as a named co-author on the study.

Entry requirements

You should have, or be studying for a degree in statistics, medical statistics, data science or statistics related degree. Familiarity with a statistical software would be useful (R, Stata, SAS, Python) but it is not essential.

Funding information

Supervisor

Dr Young Chan Kim

Description

Our group, within the Oxford Vaccine Group (OVG), is committed to the development of innovative vaccines targeting a range of emerging infectious diseases, including alphaviruses, Plague, Q-fever, and Chagas disease. Our mission is to harness cutting-edge vaccine platforms to address these global health challenges, with a primary focus on improving human health. We employ a diverse range of vaccine technologies and these are utilised to design, develop, and carry out both pre-clinical and clinical testing of novel vaccines.

In this project you will study the immune responses elicited by the novel vaccines against Chagas disease and Plague in preclinical mouse model using methods such as ELISA, ELISpot and Flow-cytometry. You may also have the opportunity to gain experience in mammalian cell culture and molecular biology techniques (such as PCR, cloning, real-time qPCR, western blot).

Outcomes

You will have the opportunity to learn a variety of basic laboratory skills applicable in many laboratory contexts in addition to project specific skills, analytical techniques, project management and critical thinking. You will also receive mentorship and guidance if you are interested in pursuing a career in biomedical research.

Entry requirements

You should have a biology or scientific background. However, technical training will be provided.

Funding

Supervisor

Professor Fumiko Esashi

Description

In many animals and plants, every chromosome contains a unique structural region, called the centromere. The centromere recruits the kinetochore machinery, which ensures proper segregation of chromosomes when cells divide. Curiously, the centromeric DNA sequences are least conserved even between closely related species, but they are commonly composed of arrays of repetitive elements in animals and plants. We study why and how these repeats have evolved at centromeres, with a specific focus on the mechanism called homologous recombination (HR).

HR is an evolutionarily conserved mechanism that catalyses homology-directed repair of DNA breaks and is essential for cell survival. Surprisingly, our recent study has revealed that centromeres harbour unusually high levels of intrinsic DNA breaks even in non-cycling cells, driving hyper-recombination. Building on this observation, the project aims to elucidate how centromeric DNA breaks impact on the fitness of human cells.

Outcomes

The student will learn to assess cellular phenotype, genetics and/or advanced imaging, depending on their primary interest, during the project. This will involve cell culture, microscopy and molecular biology. The student will also gain a clear understanding of the research field of genome stability control and centromere biology.

Entry requirements

Applicants must be studying towards, or have completed, a degree in the life sciences to be eligible for this project.

Funding information

Supervisor

Professor pedro carvalho

Description

Accumulation of misfolded proteins and aberrant protein aggregates are hallmarks of a wide range of pathologies such as neurodegenerative diseases and cancer. Under normal conditions, these potentially toxic protein species are kept at low levels due to a variety of quality control mechanisms that detect and selectively promote their degradation.

Our lab investigates these protein quality control processes with a particular focus on ER-associated degradation (ERAD), that looks after membrane and secreted proteins. The ERAD pathway is evolutionarily conserved and in mammals, targets thousands of proteins influencing a wide range of cellular processes, from lipid homeostasis and stress responses to cell signalling and communication. We investigate the mechanisms of ERAD using multidisciplinary approaches both in human and yeast cells.

We are using CRISPR-based genome-wide genetic screens and light microscopy experiments to identify and characterize molecular components involved in the degradation of disease-relevant toxic proteins. In parallel, we use biochemical and structural approaches to dissect mechanistically the various steps of the ERAD pathways. These strategies helped us in discovering ERAD mechanisms contributing to the homeostasis of the endoplasmic reticulum, the organization of the nuclear envelope and regulation of lipid metabolism. Although we focus primarily on fundamental aspects of protein quality control, our work will shed light on how these processes are disrupted in human disease and may ultimately contribute to better therapeutics.

Outcomes

It should be possible to characterize a new effector or substrate of the ERAD pathway using biochemical and/or genetic tools

Entry requirements

A good background in Biology is desired, therefore, applicants must have completed at least an A-Level in Biology to be eligible for this project.

Funding information

Supervisor

Professor Jordan Raff

Description

Centrosomes are complicated protein machines that play an important part in organising eukaryotic cells. If human cells lose their centrosome, they usually kill themselves, and centrosome dysfunction has been linked to a plethora of human diseases—including cancer and microcephaly. Almost all cells are born with a single centrosome that grows and divides; when the cell divides, each daughter inherits one centrosome and the cycle starts again.

This project involves using sophisticated microscopes to make movies of living cells expressing fluorescently-tagged versions of the key proteins that drive centrosome assembly. These large imaging datasets will be analysed using computational methods to track how the centrosomes grow and divide and how individual proteins behave. These quantitative measurements are allowing us to better understand how centrosome growth and division are regulated during cell division and development, providing important insight into how these processes go wrong in disease.

Outcomes

You will be trained in Drosophila genetics (setting up crosses to generate living fly embryos for analysis and injection), advanced microscopy (using several different types of sophisticated microscopes), and you will learn how to analyse large imaging datasets with various computational tools. You will also have a chance to learn some molecular biology (DNA cloning, mRNA preparation) and biochemistry (protein purification). You will attend our weekly group meetings and be expected to present your work to the Group at the end of your Project.

Entry requirements

Degree requirements: Studying towards (or have studied) in any of the following subjects: medicine, biology, biochemistry, computing, or engineering. No specific skills are required, as you will be taught everything. An interest in understanding how complex biological systems work is all you will need.

Funding information

Supervisor

Dr Sally Cowley

Description

Microglia are strongly implicated in the progression of Alzheimer’s, and neuroinflammation is also a feature of other neurodegenerative diseases, including Parkinson’s and ALS. We have developed a genetically tractable system for differentiating authentic human microglia from induced Pluripotent Stem cells, which is used widely to investigate disease pathogenesis and identify new therapeutic targets.

You will join our team who are using human iPS-microglia to help investigate how the Alzheimer’s-associated aggregation-prone protein tau is taken up by microglia, how it is trafficked in these cells, and how it is released from microglia in potentially more toxic forms, including in extracellular vesicles. You will focus on one aspect of this pathway, applying relevant assays to, for example, quantify tau in specific subcellular locations.

Outcomes

The project student will learn human iPS cell culture and differentiation, isolation of subcellular fractions and/or extracellular vesicles, immunocytochemistry with associated image analysis, and cellular assays for detection of tau.

Entry requirements

You should have, or be studying for, a degree related to biomedical sciences. Knowledge of neuroscience and/or immunology would be helpful. Familiarity with tissue culture techniques would be useful but is not essential.

Funding information

Supervisor

Professor Omer Dushek

Description

T cells are important white blood cells that orchestrate immune responses. They can be activated when they recognise the molecular signatures of infections (antigens) or cancer (neoantigens). T cells do this using their antigen receptors (TCRs). When this recognition is accurate, it can lead to the elimination of pathogens or cancer cells, but when inaccurate, it can lead to autoimmunity (self-antigens) or allergy (innocuous antigens).

The ability of T cells to discriminate between different antigens depends on the binding affinity/kinetics between the TCR and the antigen. However, the difference in affinity/kinetics between the TCR and foreign vs self-antigens is unknown. Here, TCRs and antigen will be purified and their interaction studied using a biophysical technique known as surface plasmon resonance.

You will analyse data by fitting mathematical models determine binding affinity and kinetics for different interactions. The objective will be to determine the difference in affinity between foreign and self-antigens.

Outcomes

You will gain valuable experience in protein production, a popular biophysical assay for binding, and mathematical modelling. The research findings may be included in a future research study.

Entry requirements

You should have, or be studying, a degree in molecular biology, biochemistry, biophysics, or biological sciences.

Funding information

Supervisor

Dr Anthony Roberts

Description

The goal of this project is to investigate how motor proteins transport cargo in eukaryotic cells, while obtaining training and experience in a variety of molecular and cell biology techniques. Our research group specialises in the motor proteins kinesin and dynein, which use ATP hydrolysis to move along microtubules. These motors transport a range of macromolecular cargo in diverse physiological processes, underscored by the severe human disorders that arise from their dysfunction.

To better understand their mechanisms of movement and regulation, we solve cryo-EM structures of kinesin and dynein complexes. From these structures we generate hypotheses, which we test by designing and introducing mutations into cultured cells using CRISPR-Cas9 genome editing. We then visualise the movement of the motors and their cargoes in mutant and wild-type cells, tagging the proteins with bright fluorescent proteins and observing their motility using advanced fluorescence microscopy. In this project, you will use these methods to generate a novel mutant and characterise its behaviour.

Outcomes

You will be trained in and have the opportunity to conduct molecular cloning, eukaryotic cell culture, and fluorescence microscopy experiments. You will gain experience in analysing sequencing data, gel images, and fluorescence microscopy time-lapse videos. You will produce figures of your data and present your findings at a friendly internal group meeting at the end of the project.

Entry requirements

You be studying for or have a degree in biochemistry, molecular or cellular biology, or a related area.

Funding information

Supervisor

Professor Matthew Freeman

Description

We study membrane proteins and how they control signalling and cellular responses to stress. These processes are implicated in multiple human diseases including cancer, neurodegeneration, inflammation and infection so, although we mostly do discovery science, our work has wide potential medical relevance, and we are also interested in the translational opportunities.

Our particular focus is the rhomboid-like superfamily. We were the first to discover rhomboids, and we proved that they were novel intramembrane proteases, conserved across evolution, and that they controlled growth factor signalling.

More recently we have become interested in the much wider superfamily of rhomboid-like proteins, the majority of which are not proteases. Of these non-protease rhomboid-like proteins, we especially focus on the iRhoms, which we discovered to be primary regulators of inflammation.

Our experimental approaches include genetics, cell biology, biochemistry and structural biology, mainly in mammalian cells but also with a variety of model systems.

Outcomes

You will gain experience with experimental cell and molecular biology, as well as participating in a research group focused on discovery science. By the end of the project, you should have completed some aspect of one of our projects. If what you do is included in a future publication you may be included as a co-author.

Entry requirements

You should be studying a mechanistic bioscience related degree (eg biochemistry, biomedical science, biology) and have an interest in research. Ideally you would be considering the possibility of a PhD as a next career step.

Funding information

Supervisor

Dr Victoria Rashbrook

Description

Congenital heart disease (CHD) is the most common birth defect, affecting 1.7% of live births worldwide. Only a third of CHD cases have a known genetic cause. Some of the remaining two-thirds of cases are caused by in utero exposure to environmental factors. One such factor is maternal high blood pressure (hypertension) during pregnancy, which has been shown in humans to double the risk of offspring CHD. However, it is not known how maternal hypertension causes CHD. In this project, we will use an animal model to investigate this problem.

In the developing embryo, the heart and placenta form at the same time. If one of these organs does not form correctly, it can cause the other organ to also develop defectively. Thus, CHD can be caused by placental defects. A high-salt diet increases blood pressure in mice. We have shown that the offspring of mice fed a high-salt diet have placental abnormalities. This may explain how maternal hypertension causes CHD. In this project, we will investigate how a high-salt diet affects placental development. We will look at the structure and blood vessels in the placentas of pregnant mice fed a high-salt diet. Techniques will include 3D modelling, tissue culture, histology, and confocal microscopy.

Outcomes

You will have the opportunity to learn several transferrable experimental techniques including dissection of placentas and embryos, high-resolution episcopic microscopy, immunofluorescent and histological staining of tissue, tissue culture and confocal microscopy.

Additionally, you will develop skills in experimental design, data analysis and interpretation. You will receive guidance and mentorship should you wish to pursue a future academic career.

We hope the data achieved in this project will eventually contribute to a publication.

Entry requirements

We will teach all of the relevant skills throughout the project. You should have a background in developmental, cardiovascular or molecular biology. We perform animal research in our lab, which you must be comfortable with.

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Supervisor

Dr David Grainger

Description

The lymphatic vascular system is a network of vessels that drains interstitial fluid (lymph), traffics immune cells and absorbs lipids. Its critical roles in homeostasis is reflected by the diseases that arise from its perturbed development and misfunction in primary lymphedema where an accumulation of protein-rich fluid results in uncontrolled swelling.

Through studying the embryonic origins and molecular cues instructing normal lymphatic development we aim to identify undiscovered causes of primary lymphedema. We are currently focussed on the role of the Bone Morphogenic Protein (BMP) signalling pathway as we have identified TLL1, a modulator of BMP signalling as a potential causative gene in primary lymphedema.

You will perform confocal imaging of whole mount and/or sectioned (cryostat and vibratome) mouse embryonic tissue by staining with immunofluorescence and RNA-fluorescence in situ hybridisation (FISH) for components of the BMP signalling pathway. Additionally, you will transfect HEK-29T cells with plasmids expressing TLL1 wildtype or mutant forms in combination with BMP signalling components followed by quantification by western blot and RT-qPCR.

Outcomes

You will learn how to study developmental and vascular biology and have a good understanding of experimental design, frequently used methods, data analysis and interpretation. Data may potentially be included in a manuscript for publication.

Entry requirements

You should have, or be studying, a biological/life sciences undergraduate degree and an enthusiastic approach to learning about our field of study and experimental techniques.

Funding information

Supervisor

Professor Clive Wilson

Description

Cell-cell communication controls almost all physiological processes in multicellular organisms, and can be mediated by soluble or lipophilic molecules. We know remarkably little about the mechanisms by which lipophilic signals are transferred between cells, even though they can play critical roles, for example in the fat droplets of breast milk.

We have developed a new system to study this process, the male accessory gland of the fruit fly, which transfers lipophilic signals to females in seminal fluid. We have found that these molecules are packaged into secreted lipid droplet-like structures called microcarriers. We have identified multiple genes that control this process, many of them linked to lipid transfer in humans, and discovered how they work.

In this project, one of the unexplored genetic mechanisms that control microcarriers will be characterised. The project will involve microdissection, genetics, high-resolution fluorescence imaging and bioinformatics.

Outcomes

You will receive training in state-of-the-art approaches that we have developed to study microcarrier formation and function. You will be contributing to characterising a mechanism that in the future might be engineered to deliver new lipophilic drugs to cells or to understand human diseases where lipophilic carriers appear to malfunction. You will work with our research team, which is also studying other signalling mechanisms that are involved in human disease, exposing you to different aspects of translational research.

Entry requirements

You should be studying a degree in the area of biomedical or biological sciences.

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Supervisor

Dr Christiana Kartsonaki

Description

The aim of the project will be to study risk factors or biomarkers for certain types of cancer. The specific objectives can be adapted to match your interests and background. The project may involve a systematic review and meta-analysis, or other literature review and/or data analysis. For example, it may be a systematic review and meta-analysis on a particular risk factor and cancer type. Alternatively it could be on the analysis of a cancer-related dataset.

Outcomes

You may have the opportunity to contribute to a paper to be submitted for publication.

You will learn how to search the literature, use the statistical software R to analyse data, plan research and perhaps write a protocol or analysis plan, and some epidemiological and statistical concepts and methods.

Entry requirements

You should be studying towards (or having completed) a degree in an academic field broadly relevant to the project and should have an interest in epidemiology, medicine, health, (bio)statistics or another related field.

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Supervisor

Dr Eirini Trichia

Description

Obesity and diabetes are major causes of death, illness and reduced quality of life globally, but with particularly marked impacts in some countries of Latin America, such as Mexico. Previous research has shown that certain reproductive traits are associated with higher risk of diabetes among women, and that this might vary by ethnicity. However, despite acknowledged challenges for women’s reproductive health in many low and middle income countries, including those in Latin America, the relevance of female reproductive factors for health and disease remain under-studied and incompletely understood in many such populations.

The Mexico City Prospective Study includes a cohort of over 100,000 Mexican women. Various data were collected for all women when they were recruited into the study, including through questionnaires, physical measurements and blood sampling. The aim of this project is to explore how various reproductive traits among women in Mexico differ according to levels of various socio-demographic and lifestyle factors, and whether these same reproductive traits are related to adiposity, blood glucose levels and potentially diabetes.

Outcomes

As well as the opportunity to gain experience of, and skills in, epidemiological research, data analysis and global health, you will produce a short research report, with the aim of submitting this for publication in a peer-reviewed medical journal.

Entry requirements

You should have, or be studying, a degree in biomedical sciences, statistics, public health or a related area. You should have an interest in epidemiology, data analysis, medical research, global health, or research in understudied populations. Some experience or interest in statistics for data analysis would be beneficial but not essential, with relevant training provided.

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Supervisor

Dr Toral Gathani

Description

The project will aim to study the associations of ethnicity with breast cancer. The project may involve a systematic review (or any other type of review) of the literature and/or data analysis. You will learn how to search the literature, use the statistical software R to analyse data, and some epidemiological and statistical concepts and methods.

Outcomes

You will be trained in searching the literature and analyse data using R. By the end of the project, you may have the opportunity to contribute to a manuscript for publication and give a presentation locally

Entry requirements

You should have or be studying medicine or other health-related degrees, such as public health and/or epidemiology.

Funding information

Supervisor

Dr Jennifer Carter

Description

Kenya has been going through a nutritional transition over recent decades, where changes in the food environment (such as access to more modern supermarkets) have occurred as the country goes through economic and social development. However, there is little evidence about how this transition has impacted diets and health.

Two projects are available that will analyse pilot data from samples of adults in traditional villages in Kenya and from ‘transitioning’ villages with access to a more modern food environment.

One project will look at the relationship between food security (eg worrying that their household does not have enough food), diet (eg as how much meat or chips participants consume) and body weight.

Another project will look at the relationships between the food environment (eg access to takeaway food or supermarkets), diet and body weight. If time, students can also look at relationships with blood pressure or blood sugar.

Outcomes

The aim of both of these projects is to produce a short research report (<1000 words) that might be submitted for publication as a short research letter in a global health peer-reviewed journal or as an poster presentation at a conference.

Entry requirements

A student with an interest in global health would be well suited to this project. A background in biology, medicine or nutrition would be relevant. This project will use quantitative data analysis, so experience and/or an interest in statistics would be advisable. If the student has had no prior training in statistics, this can be learned during the placement.

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Supervisor

Professor Bartlomiej Papiez

Description

Rheumatoid and psoriatic arthritis are two common types of inflammatory arthritis (IA) that cause joint inflammation and structural damage in patients. Radiographs of hands and feet are routinely taken and visually examined during clinical diagnosis and evaluation. Several radiographic damage quantification schemes have been proposed and adopted in clinical trials, but the complexity and expertise required limit their application in clinics.

This project aims to use deep learning methods to accurately locate joints and segment bone structures in hand radiographs, which are important steps to quantify IA-related damage. A baseline joint localisation model will be available, and you will optimise it and then utilise and adapt foundation models such as Segment Anything to perform bone segmentation. We expect the results from this project to be a proof of concept which would facilitate the development of an automated IA damage quantification pipeline.

Outcomes

You will gain knowledge of deep learning techniques for medical image analysis and experience working with foundation models and designing and implementing neural networks in Python. Depending on the results, we may use the developed methods as a foundation for future work.

Entry requirements

You should have a background in STEM and experience in machine learning and coding in Python. An interest in the clinical application of AI would be beneficial.

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Supervisor

Dr Jelena Besevic

Description

UK Biobank is a cohort study of half a million individuals in the United Kingdom. UK Biobank was set up to enable a diverse range of research into the causes and consequences of disease in middle and old age. In this project, you will work with the UK Biobank team to learn how a large epidemiological study is conducted. You will also learn how to plan research, conduct literature reviews and use statistical software to conduct data analysis. The specific aims of the project can be tailored to your research interests.

Outcomes

You may have the opportunity to contribute to scientific publications as well as presentation of your work at meetings.

Entry requirements

You should be studying a degree in biology, biomedical sciences, medicine, public health or other related study area. Experience and/or interest in statistics would be beneficial.

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Supervisor

Dr Maria Kakkoura

Description

The aim of the project will be to investigate the regional and sex-specific variations of dietary intake in China and their associations with cardiometabolic traits (eg adiposity and blood pressure). China is a socio-economically and topographically diverse country and these factors could differently affect dietary patterns and prevalence of cardiometabolic disease in various regions.

The project will utilise existing data of the prospective China Kadoorie Biobank study, which includes >0.5 million adults from five urban and five rural areas across China. The study collected blood samples and among other data, it also captured information on sociodemographic characteristics and lifestyle factors including consumption of major food groups. Anthropometric and blood pressure measurements were also performed.

You will investigate whether the relationship between food intake and cardiometabolic traits (eg body mass index, random blood glucose etc) varies among men women or among the ten diverse regions. The project can also be adapted based on your interests and background.

Outcomes

Through this project you will learn epidemiological and statistical concepts and methods, how to plan your analysis, use and analyse a large dataset using statistical software. Towards the end of the project, you will produce a short research report and you may also have the opportunity to contribute to a publication submitted in a peer-reviewed journal.

Entry requirements

You should have, or be studying, a degree in biomedical sciences, biology, nutritional sciences, medicine, statistics, data analysis, public health or other related study area.

Funding information

Supervisor

Dr Andri Iona

Description

Reproductive patterns in China have changed radically over the past decades, primarily driven by rapid socio-economic development and strict family planning policy introduced in the late 1970s. Pregnancy has a substantial physiological and metabolic impact on a woman’s body that may lead to an increased risk of cardiovascular disease (CVD), hypertension, and diabetes in later life. However, reproductive factors may also vary according to socioeconomic background and associate with adiposity traits.

The aim of the project will be to examine the associations of reproductive factors and a medical history of CVD, high blood pressure and diabetes in a Chinese cohort study of over 500,000 participants. You will investigate how these associations vary when accounting for differences in socioeconomic status and adiposity levels. Additionally you will investigate whether the effect of parenthood on health outcomes is consistent between men and women.

Outcomes

You will be trained in utilising rich and comprehensive dataset to develop and enhance your analytical skills, including statistical methods and programming techniques. This training will provide you with a solid foundation in epidemiological principles, allowing you to effectively present and interpret your findings.

At the end of the project, you will produce a short research report and deliver a short presentation. You may also have the opportunity to contribute to a paper submitted for publication in a peer-reviewed journal.

Entry requirements

You should have an interest in epidemiology, bio(statistics), data analysis, women’s health, cardiovascular disease or other related field. This project involves quantitative data analysis, so experience and/or an interest in statistics is advisable. However, during the placement, you will have the opportunity to learn these skills, including how to apply appropriate statistical methods to answer research questions, how to analyse data using statistical software, and how to interpret and present results. Applicants must be studying for, or have completed, a degree in Statistics, Public Health, Epidemiology, Health Sciences, or any related field.

Funding information

Supervisor

Dr Rachael Drewery

Description

Rates of obesity are increasing worldwide, and there are an increasing number of effective treatments to support weight loss and improve quality of life. We do not know how they work in combination or how they compare with usual care. The LightCOM trial is comparing usual NHS care with a multi-component weight loss intervention, which includes total diet replacement, medication and lifestyle support delivered by health coaches. You will contribute to a work package exploring how health coaches implement this multi-component intervention.

In support of this project, you will:

• review recordings (and transcripts) of health coach-participant consultations;
• code the content of these recordings using a fidelity checklist; and
• present these findings using basic descriptive statistics to the trial team.

Outcomes

You will develop skills and knowledge in qualitative health research methods, including coding and analysis, and basic descriptive statistics. You will have an opportunity to write a report and present findings to the wider trial team. We will also support opportunities to review or contribute to presentations and/or publications.

In addition, we will ensure that you gain broader knowledge of intervention trials, behaviour change and clinical communication.

Entry requirements

You need to have some aptitude for or interest in working with recordings and transcripts of healthcare interactions. Basic skills in qualitative research methods, audio editing software and Microsoft Excel would be an advantage. Suitable degree subjects include medicine, nursing and other allied healthcare professional training, social sciences (eg sociology, psychology, anthropology, communication studies) or degrees where you have been dealing with textual data (eg English, linguistics)

Funding information

Supervisor

Professor Rebecca Barnes

Description

The intern will contribute to an ongoing retrospective qualitative study led by the primary supervisor of the telephone management of people who were affected or at risk of COVID-19 infection. The calls were made to NHS 111 services in April 2020 in England at the start of the UK COVID-19 pandemic. The intern will be involved in the management and analysis of a unique dataset of over 250 call recordings and verbatim transcripts. The aim of this project will be to identify and code instances in the calls where clinical risk is being managed, such as when worsening advice is given.

Outcomes

Skills developed will include how to work with sensitive data, qualitative health research methods and basic descriptive statistics. Students will also gain knowledge of the management of a public health crisis, plus experience of working as a member of our friendly research team.

At the end of the project you will present your findings back to the wider group in an internal meeting. If any aspect of your analysis is included in a future publication, you may be included as a named co-author on that paper. For exceptional candidates the work may provide a grounding for a future career in research or a personal training award such as a NIHR Pre-Doctoral Fellowship.

Entry requirements

You need to have some aptitude for or interest in working with recordings and transcripts of health care interactions between patients or their family members and health care professionals. Suitable degree subjects include Medicine, Nursing, Paramedic Science, Social Sciences (eg Sociology, Psychology, Communication studies, Anthropology) or humanities (eg Linguistics, English). Basic skills in qualitative research methods and/or audio editing software would be an advantage.

Funding information

Supervisor

Dr Clara Albiñana

Description

Depression is a common mental disorder, but it presents high levels of heterogeneity, both in terms of its symptoms and molecular phenotypes. For symptoms, some individuals may struggle primarily with overwhelming sadness and low energy, while others might experience irritability, insomnia, or even physical symptoms like chronic pain. At the molecular level, depression shows a complex genetic architecture, with thousands of genetic associations of small effect and neurotransmitter and hormonal imbalances, differential inflammation and immune responses etc. However, it is unknown how the clinical and molecular phenotypes of depression intersect.

The project aims to investigate the overlap between clinically and biologically defined subtypes of depression in the UK Biobank. In practise, to goal is to combine mental-health questionnaire data together with blood multi-omic data (genomics, metabolomics, proteomics, blood biomarkers) and apply unsupervised clustering algorithms to identify subgroups of depression cases. Identifying these subgroups might lead to better diagnosis and treatment options for these patients.

Outcomes

You will have the opportunity to work alongside a postdoctoral researcher and participate in an engaging research environment. You will gain experience in analysing large biological datasets and train a range of machine learning techniques in a very active research field. At the end of the project you will present your findings back to the group in an internal meeting. If any aspect of your analysis is included in a future publication, you may be included as a named co-author on that paper.

Entry requirements

You should have, or be studying, a degree in biology, biomedical sciences, medicine, statistics, public health or other related study area. You should have experience in R or python. This project will use quantitative data analysis, so experience of and/or an interest in statistics would be beneficial. If you have had no prior training in statistics, you will have the opportunity to learn these skills during the placement.

Funding

Supervisor

Professor Daniel Freeman

Description

Aim: For many patients with psychosis the world can feel anxiety-provoking and therefore they may avoid going into situations. The aim is to understand for the first time the different types of ways that anxious avoidance of everyday situations (agoraphobia) may be shown by patients with psychosis.

Methods: Analysis of the Mobility Inventory for Agoraphobia from two pre-existing large datasets from patients with psychosis in NHS clinical services. The inventory lists 27 different situations that may be avoided. Factor analysis will be used to identify the typical ways that avoidance may be shown (ie the ways the 27 situations may reduce into a smaller number of groupings). Statistical support will be provided.

Outcomes

Most importantly, supported to produce a technical report that may be submitted for publication in a peer-reviewed journal.

Training and supervision provided in factor analysis and writing up for publication.

Time spent in a clinical psychology research group, learning about the different types of research conducted and future pathways.

Entry requirements

Applicants must be studying toward, or have completed a degree in, Psychology. It would also suit someone potentially interested in studying and/or treating mental health disorders.

Funding information

Supervisor

Dr Alexandra Hendry

Description

Early Executive Functions (EF) performance during toddlerhood has some predictive associations to later EFs and broader outcomes. Yet there is little consensus on the nature and stability of these foundations; arguably due to limitations of task design and analytic approach.

The traditional approach to EF measurement is to attribute scores on any particular task to one or two aspects of EF. Hence tasks become known as ‘inhibitory control tasks’, or ‘working memory tasks’. Yet, toddlers often have consistent response styles across tasks with supposedly different EF demands. Some toddlers struggle to complete tasks because they are overwhelmed by frustration when their attempts are unsuccessful. Others perseverate on just one strategy, or impulsively produce the first response they are able. Others seem to deploy a trial-and-error basis without ever demonstrating a consistent strategy. Additional common issues are inattentiveness, and low motivation to attempt a challenging task. Overcoming frustration, perseveration and impulsivity, employing metacognitive strategies to deduce a rule from error patterns, and sustaining attention and maintaining effort on an abstract goal are all important aspects of early EF. By reducing performance to one single score, we miss the opportunity to identify strengths and difficulties in these important skills.

In this project we will operationalise how different response styles related to the dimensions listed above would manifest across a battery of EF tasks. We will create coding schemes for each relevant response style for each task, based on patterns in trial-by-trial scores, alongside global behaviour. We will then test whether convincing evidence for cross-context and longitudinal stability of EF in toddlerhood is found when response styles are considered, rather than performance scores alone.

Outcomes

You will be given the opportunity to develop insight and hands-on experience in developmental cognitive psychology. Specifically you will be trained in behavioural coding, and given access to observational data collected from both neurotypical and neurodivergent toddlers. You will be supported to conduct appropriate statistical analyses of your data.

At the end of the project you will present your findings back to the group in an internal meeting. If any aspect of your analysis is included in a future publication, you may be included as a named co-author on that paper.

Entry requirements

You should have, or be studying, a psychology or related degree. This project would suit someone with an interest in early cognitive development. Attention to detail is a must.

Funding information

Supervisor

Dr Lucy Foulkes

Description

I am currently developing a new science communication project – a website called the Museum of Mental Health in the Media. The Museum is a curated collection of portrayals of mental health problems in popular media (eg films, TV shows, music). We are working with web developers to create the website, with input from a young person’s advisory group (YPAG). The website will be live by spring 2025. However, we need help to grow the website after that and to promote it widely, including on social media.

We are therefore seeking an intern who will help with a number of tasks: find depictions of mental health problems in popular media, convert our list of existing examples into website-ready content, and create social media posts to advertise the website. The intern will gain skills in accessible writing for general audiences, basic website development, and social media post design using Canva.

Outcomes

You will have the opportunity to gain experience in public science communication, website development and social media management. You will learn about an urgent and quickly-developing area of mental health science – understanding the impact of the changing public conversation about mental health problems. You will gain skills in writing engaging, accessible copy for the website and for social media. You will have the opportunity to meet and learn from other researchers working in this area.

At the end of the project, you will present your findings back to the group in an internal meeting and have the opportunity to write a publicly-shared blog post about your experiences. You will be credited by name on the final published website.

Entry requirements

You should be working towards, or have completed, a BSc psychology undergraduate degree, with at least a predicted high 2:1. You should have an interest in clinical psychology and mental health. You should be an excellent writer, ideally with previous experience writing for general audiences. You should enjoy the public communication of science, including via social media. You should be a self-starter with the ability to work both independently and in a team.

Funding information

Supervisor

Dr Hisashi Hashimoto

Description

Organ transplantation represents a vital solution for individuals suffering from end-stage organ failure. While immunosuppressive drugs are essential for preventing rejection of transplanted organs, their effectiveness is often compromised by severe side effects, including cardiovascular complications and nephrotoxicity. Regulatory T cells (Tregs), a specific subset of helper T cells (CD4 T cells), play a crucial role in regulating unnecessary immune responses. Our team is leveraging Tregs as a form of cellular therapy to prevent rejection of transplanted organs and is currently involved in a Phase 2 clinical trial of this approach.

We will conduct an in-depth analysis of the behaviour of human Tregs in various extracellular environments, thereby providing further insights into Treg cellular therapy. This will involve several in vitro studies, including the culture of human samples, flow cytometry analysis, and immunoassays such as ELISA.

Outcomes

As an intern, you will be trained in establishing in vitro experiments and essential research methodologies, including flow cytometry and immunoassays. You will gain hands-on experience in cell culture and data analysis, alongside insights into translational medicine and current advancements in organ transplantation immunology. This experience will enhance your scientific expertise and improve your critical thinking and problem-solving skills within a collaborative research environment.

Entry requirements

Applicants should be studying towards, or have completed, a degree related in medicine or related to immunology. Candidates should have a basic understanding of immunology and demonstrate a high level of motivation. A medical background is not essential. Candidates interested in translational medicine, basic science at the PhD level, or those with a focus on clinical studies would be well-suited for this course.

Funding information

Supervisor

Dr Letizia Lo Faro

Description

Kidney transplantation is the best treatment for end-stage kidney disease. However, there exists a great disparity between organ supply and demand. This imbalance has led to the increased use of “marginal” organs, from older donors or donors with co-morbidities, which are more prone to injury. Mitochondria are cellular organelles responsible for energy production. They are generally deeply affected during transplantation and are often the first targets of injury. Our previous work has shown that mitochondrial and related metabolic dysfunction are associated with kidney injury at time of organ donation, and might contribute to chronic organ damage.

In this project you will use clinical samples (kidney tissue) from deceased kidney donors and will investigate markers of mitochondrial dysfunction using immunoassays, such as western blotting and immunofluorescence. The levels of these markers will then be associated with clinical parameters such as the organ donor age, the kidney function after transplantation etc to investigate how these molecular markers contribute to kidney injury.

Outcomes

You will be trained in basic laboratory skills, including tissue lysis, protein extraction and quantification. You will perform immunoassays, such as Western Blotting on protein extracts and immunofluorescence on kidney tissue on microscopy slides. You will learn how to analyse results from these experiments and will gain some expertise in biological statistical analysis. You will participate in the day-to-day life of the lab, presenting your work in internal meetings.

If any aspects of these analyses will be included in scientific publications you may be included as a co-author of the manuscript.

Entry requirements

You should have, or be studying, a relevant subject degree (Biological sciences, Biomedical sciences, Biochemistry, Medicine etc). Previous experience working in a scientific laboratory would be an advantage, but it is not required.

Funding information