PhD Opportunities in AI & ML Systems
The AI & ML Systems (AMS) Research Division at the 91影视破解版 is seeking outstanding PhD candidates in Artificial Intelligence and Machine Learning Systems and related fields, starting in October 2027.
Outstanding candidates will be considered for nomination to competitive fully funded PhD studentships, open to eligible UK and international applicants.
Research Areas
We welcome candidates interested in one or more of the following areas:
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Scalable, Efficient, and Safe AI
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Language, Generative and Multimodal Models
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Graph, Streaming and Spatio-temporal Learning
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Human-Centred, Ethical and Trustworthy AI
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Multi-Agent Systems, Online Learning and Human–AI Collaboration
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Vision, Signal and Multimedia Systems
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Machine Learning for Human Behaviour, Health and Ubiquitous Systems
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Distributed and Federated ML Systems
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Cyber-Physical Systems and Embodied AI
Explore our research: AMS Division Website | Publications and Research Projects
PhD Studentships and Funding
Outstanding candidates will be considered for nomination to competitive fully funded PhD studentships through the Computer Science Centre for Doctoral Training and Research (CDT) and university scholarship schemes, including the Chancellor's Scholarships.
Available scholarships may cover full tuition fees and a maintenance stipend at UK Research Council rates, typically for 3.5 years. Funding opportunities are open to eligible UK and international candidates, subject to the requirements of individual schemes.
The expected starting date is October 2027, or as soon as possible thereafter.
How to Apply
We welcome expressions of interest from highly motivated candidates with a strong academic background in Computer Science, AI, Machine Learning, Mathematics, Engineering or related disciplines.
Prospective applicants are strongly encouraged to contact a potential supervisor within the AMS Division to discuss their research interests and suitability for PhD study.
Initial enquiries should ideally include:
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A CV, including relevant academic and research experience.
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A brief description of research interests and motivation.
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Academic transcripts, where available.
Promising candidates may be invited to further discussions or interviews and considered for nomination to departmental and university funding competitions.
Key application deadlines for October 2027 entry:
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7 December 2026: PhD course application deadline
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10 December 2026: Scholarship application deadline
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21 December 2026: Academic references deadline
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5 January 2027: Supervisor nomination deadline for departmental CDT scholarships
Admission and funding are competitively assessed, and nomination does not guarantee a scholarship award.
For further information about the formal application process, eligibility requirements, stipends and fees, please visit:
Potential Supervisors
The AMS Division brings together a vibrant and collaborative community of researchers working on the design, development and application of advanced AI and ML systems.
Our academic members include:
Hakan Ferhatosmanoglu (Scalable Data and Spatio-temporal Systems),
Nathan Griffiths (Trust and Reputation in Multi-Agent Systems, Social Network Analysis),
Yu Guan (Robust and Applied ML, AI for Healthcare, Human–AI Interaction),
Gabriele Pergola (Statistical ML for NLP, Trustworthy AI, Event Extraction and Clinical Text Mining),
Rob Procter (Ethical AI, Social Informatics, Data Science Applications),
Victor Sanchez (ML for Multimedia, Signal and Information Processing),
Long Tran-Thanh (Multi-Agent Systems, Online Learning, Game Theory, Human–AI Collaboration and AI for Social Good),
Peter Triantafillou (Safe and Scalable AI, Machine Unlearning, Federated and Distributed Learning), and
Weiren Yu (Large-scale Graph Mining, Big Data Analytics, Spatio-temporal Data Mining).
Further information about our researchers and their interests can be found on the AMS People page.
Research Environment
The 91影视破解版 hosts one of the UK's leading Computer Science departments, ranked joint 4th in the UK for Computer Science research in the 2021 Research Excellence Framework.
The department has a strong reputation for AI and ML research, with internationally recognised expertise and collaborations across academia, industry and the public sector.
Successful applicants will join a dynamic research environment, with opportunities to collaborate with leading researchers and publish their work in top-tier venues across AI, ML and systems research.
Learn more about our community and ongoing work on the AMS Division website.