Fundamentals of AI (EIT CDT)
About the course
Fundamentals of AI (EIT CDT) is a research-based DPhil course focused on foundational AI, machine learning, and computational statistics. Students will help shape the future of AI and Machine Learning with a view to real-world impact.
The Ellison Institute of Technology (EIT) Centre for Doctoral Training (CDT) in Fundamentals of AI is dedicated to advancing foundational research in artificial intelligence and machine learning, focusing on theoretical underpinnings and methodological innovation. The CDT's aim is to develop AI technologies with the potential to drive transformative impact across key global challenges aligned with the missions of Ellison Institute of Technology.
The course will provide you with training in both cutting-edge AI research methodologies and the development of business and transferable skills. You will work with leading academics at the University of Oxford and will have the opportunity to work closely with project teams at EIT with access to both university and EIT facilities. You will undertake a significant, challenging and original research project, leading to the award of a DPhil.
While there can be many definitions of the fundamentals of artificial intelligence (FoAI), within the FoAI CDT, it is defined in three areas that allows a modern, inclusive and diverse interpretation of FoAI.
- Theory and Foundations: Researchers in this area focus on the foundational mathematical, statistical, and computational principles that underpin AI. This includes research in topics such as learning theory, optimisation, stochastic analysis, complexity theory and formal methods. The aim is to create formal frameworks for the analysis of AI algorithms and systems in order to gain insight into properties, understand behaviours and to develop improved algorithms that could have widespread general use in the field.
- Applied Fundamentals: At the FoAI CDT, researchers maybe interested in particular applications of AI relevant to EIT’s Humane Themes and Scientific Programmes. Researchers in this area will examine how scientific challenges and the properties of real-world data can guide the reformulation of existing AI algorithms or the design of new algorithms entirely. Topics in this area include physical and process modelling, how to handle missing data, multimodal data integration, decision support, etc.
- Fundamentals of AI Systems and Engineering: In recent years, there has been an unprecedented emergence of large and complex AI systems, such as Large Language Models. Researchers in this area are interested in the formal frameworks for characterising the design and development of such systems and using these to further understand the properties and behaviours of such systems. They may also be interested in the security, scalability and physical resource requirements of such systems.
To learn more about the research topics you’ll have the opportunity to explore, please refer to the Research areas section on this page.
During the first year of the course you will take a number of taught courses.
The CDT directors will meet with students individually during induction and throughout the first year to create personal development plans to help identify training which would be of particular benefit.
You will undertake two 10-week exploratory projects usually with different supervisors. Towards the end of the first year, you will select a DPhil research project which may be a continuation of one of the short rotation projects, a topic from the group projects or something different.
All projects (group, rotation & DPhil) will focus on underpinning theory and method development of Artificial Intelligence and machine learning that will have the potential to have a transformative impact across a range of themes associated with EIT.
In the second year, you will move to the academic department of your main supervisor and commence your main research project.
Attendance
The course is full-time and requires attendance in Oxford. Full-time students are subject to the University's Residence requirements.
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 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, as well as guidance on what technology to bring with you as a new student at Oxford.
All students will receive a laptop.
You may have opportunities to access EIT resources and are encouraged to work closely with EIT research teams with possibilities to spend time on site at their hubs.
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 will be able to return to the MPLS Doctoral Training Centre (MPLS DTC), on Keble Road, to use the facilities there.
EIT's AI researchers will be contributing towards the individually-tailored training in advanced AI techniques and software development as part of the CDT's wider training efforts. EIT researchers are engaged in internationally leading scientific research projects underpinned by cutting edge development of AI and machine learning techniques which will engage, educate and support students in their learning.
In the event of the need for pastoral care, support is available from your college, from the project supervisor, the MPLS DTC, and the CDT management team. You will have access to seminars in all four 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.
EIT Leadership and Innovation Programming Training Students in the CDT will also have access to EIT leadership and innovation training to support them through to graduation and beyond. With a core focus on skills building, this programming is designed to develop leadership in the context of science and technology. The programme encourages students to think critically about their role as future scientific leaders and innovators. Through a combination of expert talks, practical workshops, and peer discussions, students will have the opportunity to learn directly from leading entrepreneurs and innovators representing a diverse range of sectors.
Supervision
The allocation of graduate supervision for this course is the responsibility of the EIT CDT in Fundamentals in AI 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 CDT.
During your first year, you will be allocated a supervisor from the CDT's academic leadership team. This supervisor will act as a mentor throughout the programme. Students normally have the opportunity to meet with their supervisor at least once every two weeks, averaged across the year. These meetings will serve to monitor academic progress as well as to discuss any academic issues or questions arising.
In your second year, you will be allocated a main supervisor for your DPhil project and you will transition into their academic department where you will commence your research project. This supervisor is expected to be a member of the FoAI Supervision Pool. Students are encouraged to include additional co-supervisors from EIT. Additional co-supervision may also be arranged with Oxford academics beyond the supervisor pool.
Assessment
Taught courses are generally assessed by a presentation in small groups on the material studied. Each of the two rotation projects will be assessed by researchers from the supervisor pool on the basis of a report written by the student. The year-long group project will be assessed by a joint presentation around the end of the first year.
All students will be initially admitted to the status of Probationer Research Student (PRS). Within a maximum of six terms, students will be expected to apply for transfer of status from Probationer Research Student to DPhil status.
A successful transfer of status from PRS to DPhil status will require the submission of a thesis outline. Students who are successful at transfer will also be expected to apply for and gain confirmation of DPhil status to show that their work continues to be on track. This will need to be completed within ten terms of admission.
Both milestones normally involve an interview with two assessors and therefore provide important experience for the final oral examination. Students will be expected to submit a thesis at four years from the date of admission.
The final thesis is normally submitted for examination during the fourth year and is followed by the viva examination. The final award for Oxford based students will be a DPhil awarded by the University of Oxford.
To be successfully awarded a DPhil you will need to defend your thesis orally (viva voce) in front of two appointed examiners.
Graduate destinations
This is a new course and there are no alumni yet. The CDT is dedicated to providing the organisation, environment and personnel required to develop a new generation of data scientists equipped to for a wide range of career paths in academia, research and industry.
Changes to this course
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.
Research areas
Areas of research
Foundations
Researchers in this domain are primarily focused on deep mathematical analysis for the development and further understanding of concepts that have potential broad application to AI such as learning theory, optimisation and stochastic analysis. They may also undertake mathematical analysis of AI methods whose utility have been demonstrated through empirical studies but where theoretical insight has been absent.
Applied
Researchers in this domain are inspired by real-world problems and will focus on developing substantial modifications of foundational concepts to match the particular needs of applications examining issues such as multimodal data integration, missing data, experimental design and causality. They may consider existing heuristically designed AI methods that have demonstrated high performance in applications and reformulate using foundational concepts to improve and extend the use of these approaches.
Systems
Researchers in this domain are concerned with the design, deployment and/or maintenance of large scale AI systems. They could apply formal analysis to understand the properties of such AI systems or substantially adapt and develop foundational concepts to assist in the design of better systems. Research may address topics such as scalability, resource use, safety and algorithmic fairness.
Further information
Examples of research projects can be found on the department's website.
Course components
Compulsory modules
You will take the following training course and modules:
Software Engineering Training
Training will begin with an immersive module in software engineering that will lay the foundation for a year-long, team-based open-source software development project. This course introduces software engineering and is offered to all 1st year students at the MPLS Doctoral Training Centre. It covers the main software architecture paradigms: procedural, object-orientated and functional programming, version control with Git, testing and continuous integration, project packaging and containerisation, an intro to using HPC clusters and computational workflows with snakemake.
Fundamentals of AI I: Foundational Concepts.
This module provides a rapid introduction to key topics that underpin modern artificial intelligence research. The objective is to provide an understanding of the fundamental concepts that underpin the current state of the art and to be able critically assess how their DPhil can contribute to advancing knowledge. The module will provide students with an awareness of a breadth of concepts that will allow them to make connections between areas during their DPhil and beyond. Topics will include areas such as Learning theory, Bayesian methods, Reinforcement Learning and Diffusion Processes.
Fundamentals of AI II: Modern Statistical Concepts
This module introduces you to current research developments at the interface between Statistics and AI, while also providing an opportunity to interact with module leaders and ECRs from the Department of Statistics and engage with their research areas and interests. The module will cover topics such as Bayesian Uncertainty Quantification, Statistical Wrappers for Black-Box ML Methods and Deep Generative Modelling.
Emerging Research and Skills
These will be short sessions led by the leading academics in our supervision pool. They will expose you to some of the cutting-edge research in AI at the University and give you opportunities to connect with the researchers. Many of you may have ideas about what you want to do now, but we hope these sessions will highlight areas and topics that you have not considered before and trigger new ideas.
Wider AI skills training
These sessions will be looking at areas such as data management, high-performance computing, research publishing, ethics and regulation.
Group projects
Early on in your first term, you will work in a team to consider a substantive AI problem that you will work on together throughout the first year. This will be a chance for you to engage closely with EIT teams early in your DPhil. These projects will be one of your main occupations during the second term of the first year. Time will be set aside to continue working on these projects during the third term and the summer alongside your individual projects.
Rotation projects
You will undertake two individual rotation projects between April and September (with time set aside to keep the group projects going). These will be carried out under the supervision of academics from the supervisor pool but you will be encouraged to include additional co-supervisors from EIT. Additional co-supervision may also be arranged with Oxford academics beyond the supervisor pool. During this time, you will be based in the home department of the rotation project supervisors.
DPhil project
In the second year, you will move to the academic department of your main supervisor and commence your main research project.
Further training opportunities
EIT Leadership and Innovation Programming Training (Years 1-4)
Students in the CDT will have access to EIT leadership and innovation training to support them through to graduation and beyond. The programming is built around key principles that nurture holistic growth and empower students to lead with purpose and innovation: Leadership Development, Innovation and Entrepreneurship, Community and Personal and Lifelong Development. The programme aspires to cultivate a lifelong network of impact-driven leaders and innovators. The training emphasises self-leadership, personal values and the skills needed to lead others and systems. The programme will provide students with access to top innovators and experts, along with opportunities to learn both the theory and practice of entrepreneurship. The training is delivered through a variety of formats, including expert talks, practical workshops and peer discussions.
MPLS Doctoral Training Centre Research and Professional Skills Training (Years 1-4)
Studying for a DPhil requires an aptitude for original, independent and critical thinking, as well as the ability to write papers, present data and manage projects. The Research and Professional Skills programme, which runs throughout the four years at the Doctoral Training Centre, is designed not only to equip students with the necessary skillset to carry out their research at Oxford but also provides an opportunity to develop personal transferable skills. Through a series of lectures and seminars students will be able to improve their competence and confidence as researchers. These qualities are not only key in research but equally important in many careers. Research and Professional Skills training covers scientific methodology, public engagement with science, reading scientific literature across disciplines, scientific writing, poster production, publishing a research paper, presentation and communication skills, management skills, managing your DTC DPhil, IP and commercialisation of research, research ethics, introduction to entrepreneurship, interview techniques and career development.
Entry requirements for entry in 2026-27
Proven and potential academic excellence
The requirements described below are specific to this course and apply only in the year of entry that is shown. You can use our guidance to help you evaluate whether your application is likely to be competitive.
We know that contextual factors can make it difficult for candidates to demonstrate their full potential. This course is taking part in an initiative to use contextual data to help us to better understand your achievements in the context of your individual background. For further details, please refer to the information about improving access to graduate study in the How to apply section of this page.
Please be aware that any studentships that are linked to this course may have different or additional requirements and you should read any studentship information carefully before applying. Contextual data may also be used in the assessment of studentships.
Degree-level qualifications
As a minimum, applicants should hold or be predicted to achieve the following UK qualifications or their equivalent:
- a first-class or strong upper second-class undergraduate degree with honours in statistics, mathematics, computer science, engineering, physics or a closely related subject.
Entrance is highly competitive and most successful applicants have a first-class degree or the equivalent.
A previous master's degree is not required, but it is expected that most applicants with a ‘physical science’ background will have completed a four-year integrated master's course. The undergraduate degree requirement may be alternatively demonstrated by strong performance in a relevant master's degree.
For applicants with a bachelor's degree from the USA, the minimum overall GPA that is normally required to meet the undergraduate-level requirement is 3.6 out of 4.0. However, most successful applicants are expected to have a GPA of 3.8 or above.
If your degree is not from the UK or another country specified above, visit our International Qualifications page for guidance on the qualifications and grades that would usually be considered to meet the University’s minimum entry requirements.
GRE General Test scores
No Graduate Record Examination (GRE) or GMAT scores are sought.
Other qualifications, evidence of excellence and relevant experience
Professional experience, especially research experience in artificial intelligence, is valuable and will be taken into consideration as a substitute for an academic qualification. Applicants must be able to demonstrate, in their statement of purpose and/or CV section of the application form, that they are highly numerate and capable of graduate level research in mathematics and computer science to complete the course. Prior research experience that has resulted in journal or conference publications should be included if present.
The department is looking for applicants whose research interests are aligned with its mission and whose academic and professional experience to date meet the following specification:
- Delivered an outstanding performance in an undergraduate or postgraduate degree in a subject that involves the extensive study of relevant graduate-level mathematics: We are looking for individuals with an exceptional academic track record who can demonstrate a high level of performance in a subject of study that involves graduate-level mathematical study. This would normally involve successfully completing undergraduate and possibly further postgraduate study in subjects such as mathematics, statistics, engineering, computer science or physics.
- Have demonstrable experience of artificial intelligence research: We are looking for individuals to provide evidence of their interest and commitment to artificial intelligence research commensurate with their career stage. This could involve research projects as part of their formal academic studies, internships or professional work experience.
- Possess a clear motivation for the study of fundamentals of artificial intelligence: We want to understand how your career record and experiences to date have led to an interest in the further study of the fundamentals of AI. We want to see a compelling vision for how this CDT will support your future aspirations.
- Demonstrates an understanding of how the fundamentals of artificial intelligence links to real world impact: While not all FOAI CDT students will have a deep interest in applications of AI and may prefer to focus on theoretical studies only, we want all students to have an appreciation of the link between fundamental AI research and how those outputs can be used in applications. If you are interested in applications, tell us how your interests align with the EIT themes and scientific programmes. If not, tell us how you think your theory and methods work could have a range of uses.
- Provides indicators of emerging leadership capabilities: We are seeking individuals who can demonstrate the potential to not only undertake great doctoral research but may have the ability to become leaders in their field and beyond. The CDT will develop these skills during the programme but we want candidates who can give examples where they have demonstrated strong communication skills, the ability to engage and work with others, or taken the initiative and responsibility. Evidence could be in the context of academic or professional work but can also be shown through personal interests, sports and hobbies (e.g. charity work).
English language proficiency
This course requires proficiency in English at the University's higher level. If your first language is not English, you may need to provide evidence that you meet this requirement. The minimum scores required to meet the University's higher level are detailed in the table below.
| Test | Minimum overall score | Minimum score per component |
|---|---|---|
| IELTS Academic (Institution code: 0713) | 7.5 | 7.0 |
| TOEFL iBT* including the 'Home Edition' (Institution code: 0490) | 110 | Listening: 22 Reading: 24 Speaking: 25 Writing: 24 |
| C1 Advanced† | 191 | 185 |
| C2 Proficiency‡ | 191 | 185 |
| Oxford Test of English Advanced | 165 | 155 |
*Changes to the TOEFL iBT test are being introduced on 21 January 2026. The University will not accept TOEFL tests taken from that date to meet the English language condition until a review of the revised test has been completed. Our Application Guide provides full details of the tests we accept.
†Previously known as the Cambridge Certificate of Advanced English or Cambridge English: Advanced (CAE)
‡Previously known as the Cambridge Certificate of Proficiency in English or Cambridge English: Proficiency (CPE)
Your test must have been taken no more than two years before the start date of your course. Our Application Guide provides further information about the English language test requirement.
Declaring extenuating circumstances
If your ability to meet the entry requirements has been affected by the COVID-19 pandemic (eg you were awarded an unclassified/ungraded degree) or any other exceptional personal circumstance (eg other illness or bereavement), please refer to the guidance on extenuating circumstances in the Application Guide for information about how to declare this so that your application can be considered appropriately.
References
You will need to register three referees who can give an informed view of your academic ability and suitability for the course. The How to apply section of this page provides details of the types of reference that are required in support of your application for this course and how these will be assessed.
Supporting documents
You will be required to supply supporting documents with your application. The How to apply section of this page provides details of the supporting documents that are required as part of your application for this course and how these will be assessed.
Performance at interview
Interviews are normally held as part of the admissions process and are expected to be held in February or March.
Interviews will be held online, normally with at least two interviewers from the supervision pool and one from EIT.
Prior to interview you may be required to prepare a short video highlighting your interest in a topic related to EIT and the CDT.
In some cases, you may be invited back for a second interview.
Interviews will focus on technical aspects, specifically your foundational mathematical, statistical and computational skills, your appetite to engage with cohort activities, and your commitment to innovation to solve global problems through technological advancements.
Offer conditions for successful applications
If you receive an offer of a place at Oxford, your offer will outline any conditions that you need to satisfy and any actions you need to take, together with any associated deadlines. These may include academic conditions, such as achieving a specific final grade in your current degree course. These conditions will usually depend on your individual academic circumstances and may vary between applicants. Our 'After you apply' pages provide more information about offers and conditions.
In addition to any academic conditions which are set, you will also be required to meet the following requirements:
Financial Declaration
If you are offered a place, you will be required to complete a Financial Declaration in order to meet your financial condition of admission.
Disclosure of criminal convictions
In accordance with the University’s obligations towards students and staff, we will ask you to declare any relevant, unspent criminal convictions before you can take up a place at Oxford.
Academic Technology Approval Scheme (ATAS)
This course may require you to obtain an ATAS certificate before you can apply for a visa/immigration permission. If you are offered a place, the academic department will confirm whether an ATAS certificate is required. If so, they will also send you the information you need to apply for one. You can apply for ATAS whilst your offer is conditional and before the Confirmation of Acceptance for Studies (CAS) is issued. Further information about ATAS is available on the student visa webpages.
Other factors governing whether places can be offered
The following factors will also govern whether candidates can be offered places:
- the ability of the University to provide the appropriate supervision for your studies, as outlined under the 'Supervision' heading in the About section of this page;
- the ability of the University to provide appropriate support for your studies (eg through the provision of facilities, resources, teaching and/or research opportunities); and
- minimum and maximum limits to the numbers of students who may be admitted to the University's taught and research programmes.
Funding
We expect that the majority of applicants who are offered a place on this course will also be offered a fully-funded scholarship specific to this course, covering course fees for the duration of their course and a living stipend.
For this course, we recommend that you visit our dedicated funding pages which include details of a range of external funding and loan schemes for postgraduate study. Some scholarships may also be available through our fees, funding and scholarship search tool. You should review the information carefully, including the eligibility criteria and application deadlines, noting that not all funding opportunities are available for postgraduate diploma and postgraduate certificate courses.
Details of college-specific funding opportunities can also be found on individual college websites:
Please refer to the College preference section of this page to identify which of the colleges listed above accept students for this course.
For the majority of college scholarships, it doesn’t matter which college, if any, you state a preference for in your application. If another college is able to offer you a scholarship, your application can be moved to that college if you accept the scholarship. Some college scholarships may require you to state a preference for that college when you apply, so check the eligibility requirements carefully.
Further information about funding opportunities for this course can be found on the department's website.
Costs
Annual course fees
The fees for this course are charged on an annual basis.
Fees for the 2026-27 academic year at the University of Oxford
Fee status | Annual Course fees |
| Home | £10,470 |
| Overseas | £34,700 |
What do course fees cover?
Course fees cover your teaching as well as other academic services and facilities provided to support your studies. Unless specified in the additional information section below, course fees do not cover your accommodation, residential costs or other living costs. They also don’t cover any additional costs and charges that are outlined in the additional costs information below.
How long do I need to pay course fees?
Course fees are payable each year, for the duration of your fee liability (your fee liability is the length of time for which you are required to pay course fees). For courses lasting longer than one year fees will usually increase annually, as explained in the University’s Terms and Conditions.
Graduate students who have reached the end of their standard period of fee liability will be required to pay a University continuation charge and/or a college continuation charge.
The University continuation charge, per term for entry in 2026-27 is £656, please be aware that this will increase annually. For part-time students, the termly charge will be half of the termly rate payable by full-time students.
If a college continuation charge applies (not applicable for non-matriculated courses) it will be between £150 and £500, as explained in our information about continuation charges. Please contact your college for more details, including information about whether your college's continuation charge is applied at a different rate for part-time study.
Where can I find more information about fees?
Our fees and other charges pages provide further information, including details about:
- course fees and fee liability;
- how your fee status is determined;
- changes to fees and other charges; and
- continuation charges.
Information about how much fees and other costs will usually increase each academic year is set out in the University's Terms and Conditions.
Additional costs
This course includes compulsory elements that entail additional costs beyond fees (or, after fee liability ends, continuation charges) and living costs. For those students in receipt of a full CDT studentship award, an additional research training support grant (RTSG) to cover costs of associated equipment, research and travel will be provided. Students who are not in receipt of a full CDT studentship award will need to cover these course-related costs. Individual research projects come with variable research costs and students will need to discuss these with their supervisor and plan a budget for their project. In some cases students may need to apply for additional funding, either from the RTSG or other sources. Students should always involve their supervisor with such funding requests.
Living costs
In addition to your course fees and any additional course-specific costs, you will need to ensure that you have adequate funds to support your living costs for the duration of your course.
Living costs for full-time study
For the 2026-27 academic year, the range of likely living costs for a single, full-time student is between £1,405 and £2,105 for each month spent in Oxford. We provide the cost per month so you can multiply up by the number of months you expect to live in Oxford. Depending on your circumstances, you may also need to budget for the costs of a student visa and immigration health surcharge and/or living costs for family members or other dependants that you plan to bring with you to Oxford (if dependant visa eligibility criteria are met).
Further information about living costs
The current economic climate and periods of high national inflation in recent years make it harder to estimate potential changes to the cost of living over the next few years. For study in Oxford beyond the 2026-27 academic year, it is suggested that you budget for potential increases in living expenses of around 4% each year – although this rate may vary depending on the national economic situation.
A breakdown of likely living costs for one month during the 2026-27 academic year are shown below. These costs are based on a single, full-time graduate student, with no dependants, living in Oxford.
| Lower range | Upper range | |
|---|---|---|
| Food | £315 | £545 |
| Accommodation | £825 | £990 |
| Personal items | £160 | £310 |
| Social activities | £50 | £130 |
| Study costs | £35 | £90 |
| Other | £20 | £40 |
| Total | £1,405 | £2,105 |
For information about how these figures have been calculated as well as tables showing the likely living costs for nine and twelve months, please refer to the living costs page of our website.
College preference
Students enrolled on this course will belong to both a department/faculty and a college. Please note that ‘college’ and ‘colleges’ refers to all 43 of the University’s colleges, including those designated as societies and permanent private halls (PPHs).
If you apply for a place on this course you will have the option to express a preference for one of the colleges listed below, or you can ask us to find a college for you. Before deciding, we suggest that you read our brief introduction to the college system at Oxford and our advice about expressing a college preference.
If you are a current Oxford student, and your college does not accept applications for this course, it will not be possible to ask your current college to make an exception. Due to the additional support arrangements for this course, applicants will only be placed at the colleges listed below.
The following colleges accept students on the EIT CDT in Fundamentals of AI:
Before you apply
Our guide to getting started provides general advice on how to prepare for and start your application, including advice to help you evaluate whether your application is likely to be competitive.
If it is important for you to have your application considered under a particular deadline – eg under the January deadline in order to be considered for Oxford scholarships – we recommend that you aim to complete and submit your application at least two weeks in advance. Check the deadlines on this page and the information about deadlines and when to apply in our Application Guide.
Application fee waivers
An application fee of £20 is payable for each application to this course. Application fee waivers are available for the following applicants who meet the eligibility criteria:
- applicants from low-income countries;
- refugees and displaced persons;
- UK applicants from low-income backgrounds; and
- applicants who applied for our Graduate Access Programmes in the past two years and met the eligibility criteria.
You are encouraged to check whether you're eligible for an application fee waiver before you apply.
Readmission for current Oxford graduate taught students
If you're currently studying for an Oxford graduate taught course and apply to this course with no break in your studies, you may be eligible to apply to this course as a readmission applicant. The application fee will be waived for an eligible application of this type. Check whether you're eligible to apply for readmission.
Application fee waivers for eligible associated courses
If you apply to this course and up to two eligible courses during the same application cycle, you can request an application fee waiver so that you only need to pay one application fee. We recommend that you use your application fee waiver to apply only for eligible courses that are closely related in research area to this one.
To be considered eligible for an application fee waiver, each additional course must be:
- doctoral level eg a Doctor of Philosophy (DPhil) or Centre for Doctoral Training (CDT) course; and
- offered by one of the departments in the MPLS Division or one of the departments in the Medical Sciences Division.
If this is the first eligible course that you are applying to, you can request an application fee waiver for an additional course after you have submitted your application for this course. If you have already applied to another course that the meets the eligibility criteria shown above, you should request an application fee waiver before starting an application to this course.
Remember to state clearly in your request which course(s) you intend to apply to. If your request is successful, you will receive an application fee waiver code that is valid for this admission cycle (ie for entry in the 2026-27 academic year). Our Application Guide provides instructions for entering your application fee waiver code.
Do I need to contact anyone before I apply?
You do not need to contact anyone at the University prior to submitting your application. However, if you do have questions, informal enquiries should be made to the EIT CDT in Fundamentals of AI administrator in the first instance (See Further information and enquiries).
You are not expected to contact academic members of staff before applying and you will not be required to name any potential supervisors on your application form.
Improving access to graduate study
This course is taking part in initiatives to improve the selection procedure for graduate applications, to ensure that all candidates are assessed fairly.
Contextual data (where it has been provided in the application form) and your contextual statement (if you choose to provide one) will be used as part of an initiative to contextualise applications at the different stages of the selection process. When academic shortlisting takes place, we will use also information on ethnicity as part of an initiative to ensure that applicants who identify as Black British and meet the relevant criteria are invited to interview.
Completing your application
You should refer to the information below when completing the application form, paying attention to the specific requirements for the supporting documents.
For this course, the application form will include questions that collect information that would usually be included in a CV/résumé. You should not upload a separate document. If a separate CV/résumé is uploaded, it will be removed from your application.
If any document does not meet the specification, including the stipulated word count, your application may be considered incomplete and not assessed by the academic department. Expand each section to show further details.
Proposed field and title of research project
Please leave 'Field and title of research project' blank on the 'Course' tab of the application form.
Proposed supervisor
It is not necessary for you to identify a potential supervisor in your application.
Referees:
Three overall
Whilst you must register three referees, the department may start the assessment of your application if two of the three references are submitted by the course deadline and your application is otherwise complete. Please note that you may still be required to ensure your third referee supplies a reference for consideration.
If you include an employer as a referee, they must be familiar with your work over the last few years from a technical perspective and be able to comment on technical work that you have undertaken. They should be able to explain why you are a good fit for the course.
Your references will be assessed for your:
- intellectual ability
- academic achievement
- motivation and interest in the subject area
- ability to work effectively both in a group and independently.
Official transcript(s)
Your transcripts should give detailed information of the individual grades received in your university-level qualifications to date. You should only upload official documents issued by your institution and any transcript not in English should be accompanied by a certified translation.
More information about the transcript requirement is available in the Application Guide.
Contextual statement
If you wish to provide a contextual statement with your application, you may also submit an additional statement to provide contextual information on your socio-economic background or personal circumstances in support of your application.
It is not necessary to anonymise this document, as we recognise that it may be necessary for you to disclose certain information in your statement. This statement will not be used as part of the initial academic assessment of applications at shortlisting, but may be used in combination with socio-economic data to provide contextual information during decision-making processes.
Please note, this statement is in addition to completing the 'Extenuating circumstances’ section of the standard application form.
You can find more information about the contextual statement on our page that provides details of the continuing pilot programme to improve the assessment procedure for graduate applications.
Statement of purpose:
A maximum of 1,200 words
Your statement should be written in English and should focus on your motivation, research interests and career ambitions, rather than on other personal achievements, interests and aspirations.
You must structure your statement into the six sections listed below. Please ensure that the word counts are clearly displayed. The section headings will not count towards the word count. Please be as specific and detailed as possible in your answers.
- Give an overview of your academic education and professional career to date and how it led to an interest in conducting research in the fundamentals of AI (250 words)
- Describe a research project you have undertaken that involved the development of AI theory or methods. What was the problem you addressed? What was your contribution to the development of AI? Explain why an existing, off-the-shelf solution could not be used. (Up to 400 words)
- Describe a situation where you once made a programming error. How did you discover the error? How did you trace the source of the error? And how was it resolved? (Up to 250 words)
- What makes the FoAI CDT more appropriate to you than other options for doctoral study? (Up to 150 words)
- How could your interests support one or more of the EIT themes or scientific programmes (Up to 150 words)
- If you are invited to interview, you will be asked to undertake some technical exercises. In order to help determine appropriate questions for you, please indicate one current primary area of interest from the following: (i) Foundations, (ii) Applied, or (iii) Systems. More information about these areas of interest can be found on the Research Areas section of this page. You response will be used as a guide and will not commit you to a particular area of research if you are offered a place on the course.
Please note that if if these instructions are not followed, your application will not be considered as complete and may not be considered.
You may also explain any special circumstances relating to any element of your application that you wish to bring to the attention of the assessors in your statement.
Your statement will be assessed for:
- your reasons for applying
- evidence of understanding the proposed area of study
- your ability to present a coherent case in proficient English
- your commitment to the subject, beyond the requirements of the degree course
- your preliminary knowledge of the subject area and research techniques
- your capacity for sustained and intense work
- your reasoning ability and ability to absorb new ideas often presented abstractly, at a rapid pace
- your willingness to engage with fundamental AI projects with potential to impact across a range of humane themes associated with the Ellison Institute of Technology (EIT)
Start or continue your application
You can start or return to an application using the relevant link below. As you complete the form, please refer to the requirements above and consult our Application Guide for advice.
After you've submitted your application
Your application (including the supporting documents outlined above) will be assessed against the entry requirements detailed on this course page. Whether or not you have secured funding will not be taken into consideration when your application is assessed. You can find out more about our shortlisting and selection process in our detailed guide to what happens next.
Find out how to manage your application after submission, using our Applicant Self-Service tool.