NASA satellite imagery
NASA satellite imagery
(Image credit: Philip Stier)

Intelligent Earth (UKRI CDT in AI for the Environment)

About the course

The Intelligent Earth CDT is a four-year doctoral programme designed to equip a new generation of students with advanced AI skills to tackle some of the most pressing environmental issues. 

The programme will train a new generation of quantitative environmental data scientists to make substantial contributions in environmental and data sciences through five closely connected themes:

  1. Climate
  2. Biodiversity
  3. Natural hazards
  4. Environmental solutions
  5. Core AI/ML research on complex environmental data

The programme is intrinsically interdisciplinary: you will be advised by both an environmental science supervisor and an AI supervisor from two different departments, plus a non-academic partner who also serves as host for a secondment. This course is suitable for quantitative applicants from data science, mathematical, physical and environmental science backgrounds. 

The teaching model for all courses will be tailored towards training students to become independent researchers. After introductory lectures, you will be introduced to the corresponding AI tools, frameworks and environmental datasets to apply the taught material in tutorial-based project work. You will work in interdisciplinary groups tackling grand challenges in environmental science of increasing complexity with AI. The programme will be individually tailored to your needs.

Key components of the teaching programme:

  • Induction week
  • Core courses in foundations of AI/ML and foundations of the four environmental themes
  • Responsible AI training
  • Computational skills training
  • Advanced cross-cohort courses will focus on specific areas of AI applied to grand challenges and associated datasets from the four environmental themes
  • Professional skills training
  • Teaching skills training

In the second half of year one, you will undertake a three-month research project supervised by one of the potential DPhil supervisors.

In addition to the formal teaching programme, student experience and training will be enriched by:

  • Weekly Intelligent Earth seminars
  • Annual two-week hackathons
  • Annual two-day CDT conference

Course structure

In year one, you will take core courses and computational skills training courses, followed by advanced cross-cohort courses, responsible AI training, and professional skills training modules, culminating in a three-month research project followed by the annual hackathon and conference. Course free periods will be used for consolidation, supervisor matching, and DPhil proposal development.

In year two, you will transition to your primary department and supervisors, and you will start your DPhil research. You will take advanced cross-cohort courses and professional/computational skill training modules. A secondment with non-academic partners may also take place at this stage, but may alternatively take place in year three.

In year three, your focus will be on DPhil research with optional advanced courses and professional/computational skill training modules based on your individual training needs. A secondment with non-academic partners may also take place at this stage if it was not undertaken in year two.

In year four, you will finalise your DPhil research and complete your thesis writing. Professional training will focus on career development, job/fellowship applications and interviews.

Attendance

The course is full-time and requires attendance in Oxford. Full-time students are subject to the University's Residence requirements.

One of the following departments will serve as your primary department from year two onwards, when you will begin your DPhil research:

Provision exists for students on some courses to undertake their research in a ‘well-founded laboratory’ outside of the University. This may require travel to and attendance at a site that is not located in Oxford. Where known, existing collaborations will be outlined on this page. Please read the course information carefully, including the additional information about course fees and costs. 

Resources to support your study

As a graduate student, you will have access to the University's wide range of world-class resources including libraries, museums, galleries, digital resources and IT services.

The Bodleian Libraries is the largest library system in the UK. It includes the main Bodleian Library and libraries across Oxford, including major research libraries and faculty, department and institute libraries. Together, the Libraries hold more than 13 million printed items, provide access to e-journals, and contain outstanding special collections including rare books and manuscripts, classical papyri, maps, music, art and printed ephemera.

The University's IT Services is available to all students to support with core university IT systems and tools, as well as many other services and facilities. IT Services also offers a range of IT learning courses for students, to support with learning and research.

The programme is resourced by UK Research and Innovation (UKRI) with contributions from the university and partners. It will be integrated in Oxford's Doctoral Training Centre and training may take place in a number of locations across the university and students will often work together on problem sets, or in groups, with the support of demonstrators.

You will have access to computational facilities as well as a laptop. When you move out to your department you will also have access to the facilities provided by that department. You will remain a member of the CDT and be able to return to the CDT facilities, based within the Doctoral Training Centre, on Keble Road, to use the facilities there.

You will have access to seminars in all eight departments as well as across the wider university. In addition to the training modules offered by the CDT, you will be able to sign up for a wide range of training courses and modules offered by departments across the university via the University's Researcher Training Tool.

You will also have access to Oxford's wide library network, including the recently refurbished Radcliffe Science Library.

Supervision

The allocation of graduate supervision for this course is the responsibility of the Intelligent Earth CDT and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff. Under exceptional circumstances a supervisor may be found outside the Intelligent Earth CDT.

During your first year, you will have a supervisor from the academic leadership of the CDT. Meetings with your supervisor will serve to monitor academic progress as well as to discuss any academic issues or questions arising. When you transition into one of the participating departments to commence you research project in year two, you will be co-advised by two supervisors, one from an environmental science department and one from an AI department. First-year supervisors will act as mentors throughout the programme, providing academic and pastoral guidance.

You will be expected to meet your supervisor at least once every two weeks, averaged across the year, to discuss your progress.

Assessment

You will be assessed continually throughout the first year training courses modules. In the second half you will undertake a three-month research project and will be required to deliver a written report that will be assessed.

At the end of the second year, you will be required to write a report and give a presentation on your research, and to present a detailed and coherent plan for the research-intensive phase in the third and fourth years of your doctoral studies. Progress towards completion is again formally assessed some way into the final year of study.

You will carry out your DPhil project in the department of your primary supervisor and will gain your DPhil from the department in which you carry out your research project. You will follow the same milestones and assessments as a standard DPhil, so you will have Probationer Research Student (PRS) status until you confirm your status as a DPhil student by term six. By term nine you will confirm status and you will submit your thesis for assessment by the end of term 12.

Graduate destinations

The CDT will train a new generation of quantitative environmental data scientists equipped to make substantial contributions in environmental and data sciences as well as being prepared for a wide range of career paths in academia, research and industry, supported by the CDT's extensive partnership network.

The CDT anticipates Intelligent Earth Graduates to drive innovation and found their own start-ups, supported by the programme’s dedicated training in enterprise, impact, and responsible AI.

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. The safety of students, staff and visitors is paramount and major changes to delivery or services may have to be made if a pandemic, epidemic or local health emergency occurs. In addition, in certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include illness, sabbatical leave, parental leave or change in employment.

For further information please see our page on changes to courses and the provisions of the student contract regarding changes to courses.

Was this page useful?*