Join us for a PhD

Successful candidates will join Imperial's Department of Computing and become part of a dedicated PhD cohort focused on advancing the Frontier AI Lab's mission  — tackling foundational challenges in model training, safety and societal impact.

PhD students joining the Lab will also benefit from: 

• A fully funded doctoral scholarship covering tuition fees (including overseas fees) and a monthly living stipend for 42 months. 
• The opportunity to work closely with world-leading Thomson Reuters Lab directors, research scientists and Imperial academics. 
• Access to high-quality computing infrastructure.
• Dedicated PhD administrative support.
• Annual funding to attend and present research at leading international conferences.
• Opportunities to showcase their research at Lab-organised industry-academia collaborative events. 

For more information about the benefits of joining the Lab, please do not hesitate to reach out to us. 

Frontier AI Research Lab PhD students will have the opportunity to be supervised by:

• Professor Alessandra Russo, the Lab's Director, Professor of Applied Computational Logic at Imperial's Department of Computing, and convening Co-Director of Human and Artificial Intelligence at the School of Convergence Science.
• Professor Jonathan Schwarz, the Lab's Associate Director, Visiting Professor at Imperial, and Head of AI at Thomson Reuters Foundational Research.
• An academic member of staff from Imperial's Department of Computing.

PhD students who join the Lab will also have the opportunity to collaborate with:

• Professor Felix Steffek, Visiting Professor at Imperial and Professor of Law at the University of Cambridge.
• Andrew Bean, Honorary Research Associate at Imperial and Senior Researcher at the Lab, specialising in LLM evaluation, construct validity, and algorithmic bias.
• Nabeel Seedat, Honorary Research Associate at Imperial and Senior Researcher at the Lab, specialising in data-centric AI and large language models for reliable and trustworthy machine learning.

The Frontier AI Research Lab is also pleased to offer opportunities for external co-supervision. We are delighted to announce that we currently have one PhD position available under the joint supervision of Professor Jonathan Schwarz and Professor Mihaela van der Schaar, Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge, together with supervision from an academic member of staff from the Department of Computing. 

• Applications are reviewed on a rolling basis, subject to funding availability. Therefore, we encourage you to register your interest as soon as possible. 
• Funding is available for approximately a dozen PhD students (including overseas). 
• Successful candidates will typically start in October or April, once any offer conditions are met—we are aiming to enrol the majority of the Lab's PhD cohort by October 2027. 

Initial Shortlisting

1. For initial consideration, please fill out the Lab's shortlisting form. 
2. Your responses will be reviewed by the Lab's team, including the Co-Directors and Centre Manager. 
3. If shortlisted at this initial stage, you will be invited to submit a formal PhD application through Imperial's Department of Computing, as required by all candidates.

Please note that funding is available for a approximately a dozen PhD students and therefore, the selection process is highly competitive. All initial shortlisting applications will be reviewed and assessed against the Lab and department's eligibility criteria, and the most outstanding candidates will be selected within available funding. 

Imperial Department of Computing Eligibility Criteria

Applicants are typically expected to hold a First-Class or Distinction Master's level degree (or international equivalent) in a relevant scientific or technical discipline. We therefore encourage you to familiarise yourself with the Department of Computing's PhD application guidelines, including information on alternative routes to qualification if you do not meet the standard admissions requirements. 

Research Output and Publications Record

Given the highly competitive nature of the programme and the limited number of places available, high-quality peer-reviewed publications at leading venues in Artificial Intelligence, Machine Learning, Computer Vision, and Natural Language Processing are a primary consideration during the shortlisting process. Applicants should ensure that their CV clearly highlights any publications, including authorship position, venue, and year of publication.

Examples of leading venues include, but are not limited to:

AI / Machine Learning

• NeurIPS- Conference on Neural Information Processing Systems
• ICML- International Conference on Machine Learning
• ICLR- International Conference on Learning Representations

Computer Vision (CV)

• CVPR- Conference on Computer Vision and Pattern Recognition
• ICCV- International Conference on Computer Vision
• ECCV- European Conference on Computer Vision

Natural Language Processing (NLP)

• ACL- Annual Meeting of the Association for Computational Linguistics
• EMNLP- Conference on Empirical Methods in Natural Language Processing

Broad AI Conferences

• AAAI- Association for the Advancement of Artificial Intelligence
• IJCAI- International Joint Conference on Artificial Intelligence