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The University of Exeter’s Department of Clinical and Biomedical Sciences is inviting applications for a PhD studentship funded by Diabetes UK to commence on 21 September 2026 or as soon as possible thereafter. For eligible students the studentship will cover Home tuition fees plus an annual...
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sustainability. This PhD project aims to develop new ionic conducting materials as next-generation membrane alternatives for fuel cell and electrolyser applications. Ceramic ion conductors present a promising
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by understanding how cancer risk prediction models are influenced by missing and incomplete symptom data recorded in electronic health records (EHRs) and developing methods to address any issues
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dynamic mobility of UAVs, limited onboard energy, and the stochastic nature of 3D wireless channels. Therefore, this project aims to develop novel reliable resource orchestration solutions for AEC by
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both individual decision-making and multi-agent cooperation. The student will investigate two complementary directions: ToM-Enhanced Decision-Making for Autonomous Agents: Develop decision-making
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with NEOM, one of the world’s largest ecological restoration programmes, the project will develop machine-learning approaches to analyse satellite observations of vegetation change and evaluate large
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interests, whether you prefer system-level analysis, control design, simulation-based investigation, or a combination of these. The specific research direction will be developed in collaboration with
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. This PhD project aims to develop efficient, reasoning-enhanced Vision–Language Models tailored to multimodal medical data. The main aim is to investigate how explicit clinical reasoning can be embedded
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rapid, data-driven, physically informed and human-aligned decision framework capable of robust, equity-aware intervention planning under climate uncertainty. This PhD will develop a decision-support
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can solve. While conventional electronic information processors are exceedingly well-developed, their capabilities are being rapidly outstripped by the rapid rise of AI: both the training and inference