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University of Oxford

Top university

Fully Funded DPhil Studentships in Technical AI Governance at University of Oxford University of Oxford in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Studentships are fully funded, covering tuition and a stipend. Dedicated compute funding is provided for each DPhil student. The studentships are available on a full-time basis, with possible remote and part-time arrangements for exceptional candidates.

Deadline

Dec 2, 2026

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Country

United Kingdom

University

University of Oxford

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Keywords

Computer Science
Electrical Engineering
Political Science
Health Policy
Information Security
Machinelearning
#privacy
Engineering

About this position

The University of Oxford, in partnership with the Oxford Martin AI Governance Initiative (AIGI) and the Department of Engineering Science, is offering fully funded DPhil (PhD) studentships in Technical AI Governance. These studentships are designed to train researchers at the intersection of advanced AI systems and effective governance, combining rigorous technical research with deep engagement in policy, law, and societal impact. The programme aims to bridge the gap between cutting-edge AI research and real-world governance, nurturing a new generation of scholars fluent in both AI technology and its societal implications.

Research areas for the studentships include compute infrastructure governance, privacy-preserving transparency and auditing, model evaluations and benchmarks, technical standards development, information security, AI system resilience, and interpretability for model evaluation. Students will benefit from Oxford’s world-class research facilities, including hardware accelerator clusters, robotics platforms, and advanced networking equipment. The programme is supported by leading academics such as Prof. Robert Trager, Prof. Michael A. Osborne, and Dr. Fazl Barez, and offers opportunities for collaboration with AIGI’s extensive network across governments, industry, academia, and civil society.

Applicants should have a strong background in engineering, computer science, statistics, mathematics, physics, or related technical disciplines. Those with experience in AI policy, governance, law, or political science are also encouraged to apply, provided they have a clear technical background. The studentships are available on a fully funded, full-time basis, but remote and part-time arrangements may be considered for exceptional candidates. Each DPhil student receives dedicated compute funding and access to Oxford’s exceptional technical infrastructure.

There are two routes to apply: the Direct DPhil Route (Track I), where applicants propose a project aligned with technical AI governance to either the Department of Computer Science or the Department of Engineering Science, and the AIMS-Integrated Route (Track II), which includes one year of advanced technical coursework. Applications must be completed (including references) by 2 December 2025 for departmental funding consideration. If studentships remain, applications may be considered until 3 March 2026. For Track II, the deadline is 28 January 2026. After submitting your application, you must inform the TAIG Programme Manager via email at [email protected] to ensure your application is reviewed by the programme panel.

This is a unique opportunity to join a vibrant research community at the forefront of technical AI governance, with strong support for interdisciplinary research and professional development. Graduates will be well-positioned for leadership roles in academia, industry, government, and civil society, addressing some of the most pressing challenges in AI governance today.

Funding details

Studentships are fully funded, covering tuition and a stipend. Dedicated compute funding is provided for each DPhil student. The studentships are available on a full-time basis, with possible remote and part-time arrangements for exceptional candidates.

What's required

Applicants should have a strong background in engineering, computer science, statistics, mathematics, physics, or related technical disciplines. Candidates with experience in AI policy, governance, law, or political science are also encouraged to apply, provided they have a clear technical background. Motivation to conduct technical research with direct governance impact is essential. Applications must be submitted with references by the specified deadlines. Part-time and remote options may be available for exceptional candidates.

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Engineering

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Health Policy

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Machinelearning