23 developer-"https:" "https:" "https:" "University of Aberdeen" positions at University of Exeter
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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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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
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supportive relationships? Are you a great team leader? Do you want to make a difference? We are looking for a proactive, committed and organised leader to develop our boarding provision at a time of growth
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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
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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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, organising and analysing data, supporting thematic and narrative analysis of legal judgments and statutory reports, contributing to the development of an interdisciplinary analytical framework, and assisting
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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