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Welcome to the EIT Centre for Doctoral Training in the Fundamentals of AI

The Ellison Institute of Technology CDT in Fundamentals of AI (FoAI CDT) offers students the opportunity to help shape the future of artificial intelligence and machine learning. With a focus on advancing the theoretical foundations and driving methodological innovation, the programme empowers researchers to challenge convention and push the boundaries of what AI can achieve. Our mission is to equip the next generation of researchers with the skills and vision to develop groundbreaking technologies that address some of the most pressing global challenges, anchored in the transformative goals of the Ellison Institute of Technology (EIT).

The EIT CDT in Fundamentals of AI based at the University of Oxford is part of a strategic collaboration between the University and the Ellison Institute of Technology. The programme will provide students with training in both cutting-edge AI research methodologies and the development of business and transferable skills and students are encouraged to work closely with research teams at both the university and EIT throughout their studies. 
The programme, funded by EIT Oxford, has up to 20 fully-funded studentships available per year. These are all open to applicants of any nationality. Students will undertake a significant, challenging and original research project, leading to the award of a DPhil (PhD).

Applications for 2026/27 entry are now open. The application deadline is 8 January 2026 (12:00 midday UK time) with interviews for shortlisted candidates in February/March. 

 

 

 

What are the Fundamentals of AI?

While there can be many definitions of the fundamental of artificial intelligence (FoAI), within the EIT CDT, we define three areas that allows a modern, inclusive and diverse interpretation of FoAI. All three of these areas will work towards building links between fundamental AI research and how those outputs can be used in applications and have real impact to support EIT humane themes.

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 more directly related to EIT's Humane Themes. Researchers in this area will examine how 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 how to handle missing data, multimodal data integration, decision support, etc.

Fundamentals of AI Systems and Engineering

In recent years, there has been an unprecedent 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.