Sort by
Refine Your Search
-
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...
-
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
-
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
-
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
-
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
-
network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms
-
. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
-
signals is hard. Real-world data is noisy, assumptions don't always hold, and the stakes of getting it wrong are high. You'll use and help further develop an open-source Julia-based toolkit, developed by co
-
their personal skillset to the discovery, development, and commercial translation of new 3D nanoscale magnetic metamaterials. What You’ll Do in this Project Size, weight, and power: the future is small
-
. 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