Computer Science » Research Studentships

PhD Studentships in Computer Science

Mon, 12 Oct 2026 09:51:00 GMT

The Computer Science Department offers funded scholarships each year. The scholarships cover full fees and stipend payable at current UK Research Council rates. If you would like to be considered please note the next deadlines below:

Course application deadline: Dec 7th, 2026
Scholarship application deadline: Dec 10th, 2026
References deadline: Dec 21st, 2026
Nominations by Supervisor deadline: Jan 5th, 2027

Eligibility: Scholarships are open to Home, EU, and international applicants.

Candidates should have a good degree in computer science, engineering or a related discipline, with solid mathematical background and strong programming skills. The scholarship will give you the opportunity to join a leading Computer Science department, and pursue academic excellence in your chosen area of Computer Science: Artificial Intelligence, Data Science, Human Centred Computing, Systems, Theory, or Applied Computing.

Please apply online by following our application advice.

PhD Studentship in The Department of Computer Science in collaboration with the Department of Psychology

Tue, 04 Nov 2025 08:40:12 GMT

Applications are invited for a 91�� PhD Studentship in The Department of Computer Science in collaboration with the Department of Psychology. The PhD will start October 2026 on Machine Learning and Psychophysiological Deception Detection. The studentship is part sponsored by GCHQ and funded for up to 3.5 years with fees and a stipend at the standard UKRI rate. The position is only open to Home fee status students.

PhD Positions in Theoretical Computer Science - Application deadline 11th November 2025

Mon, 13 Oct 2025 13:23:00 GMT

PhD positions are available at the Theory and Foundations group in the Department of Computer Science, 91��, UK. The group works on various aspects of theoretical computer science including:

* algorithmic game theory

* approximation algorithms

* automata and formal languages

* combinatorics and graph algorithms

* computational complexity

* logic and games

* online and dynamic algorithms

* parallel algorithms and distributed computing

* parameterized complexity and structural graph theory

* random structures and randomized algorithms

* sublinear and streaming algorithms

* theoretical foundations of machine learning