Program Overview

Introduction to the Fundamentals of AI (EIT CDT) Program

The 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.

About the Course

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.

Research Areas

The course covers three main research areas:

• Theory and Foundations: Researchers in this area focus on the foundational mathematical, statistical, and computational principles that underpin AI.
• Applied Fundamentals: Researchers in this area 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.
• Fundamentals of AI Systems and Engineering: Researchers in this area are concerned with the design, deployment, and/or maintenance of large-scale AI systems.

Course Structure

The course is full-time and requires attendance in Oxford. The first year includes taught courses, exploratory projects, and a group project. In the second year, students move to the academic department of their main supervisor and commence their main research project.

Attendance and Resources

The course is full-time and requires attendance in Oxford. Full-time students are subject to the University's Residence requirements. Students will have access to the University's wide range of resources, including libraries, museums, galleries, digital resources, and IT services.

Supervision

The allocation of graduate supervision for this course is the responsibility of the EIT CDT in Fundamentals in AI. Students will be allocated a supervisor from the CDT's academic leadership team, who will act as a mentor throughout the program.

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.

Graduate Destinations

This is a new course, and there are no alumni yet. The CDT is dedicated to providing the organization, environment, and personnel required to develop a new generation of data scientists equipped to pursue a wide range of career paths in academia, research, and industry.

Entry Requirements

The requirements for this course include:

• A first-class or strong upper second-class undergraduate degree with honors in statistics, mathematics, computer science, engineering, physics, or a closely related subject.
• Professional experience, especially research experience in artificial intelligence, is valuable and will be taken into consideration as a substitute for an academic qualification.
• English language proficiency at the University's higher level.

Funding

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.

Costs

The annual course fees for this course are:

• Home: Ł10,470
• Overseas: Ł34,700 Students will also need to ensure that they have adequate funds to support their living costs for the duration of their course.

College Preference

Students enrolled on this course will belong to both a department/faculty and a college. The following colleges accept students on the EIT CDT in Fundamentals of AI:

• Jesus College
• Kellogg College
• Linacre College
• Reuben College
• Wolfson College

How to Apply

To apply for this course, students should refer to the University's Application Guide for advice. The application form will include questions that collect information that would usually be included in a CV/résumé. Students should not upload a separate document.

Admission Status

The course is open to applications for entry in the upcoming academic year. The deadline for applications is 12:00 midday UK time on Thursday, 8 January 2026.