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, please contact Dr Isabella Guido once deadline passes. You will need to meet the minimum entry requirements for our PhD programme . We are seeking a highly motivated and skilled candidate with a
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the central challenge hindering this vision: the fundamental incompatibility between text-native LLMs and the operational reality of computer networks. Directly applying LLMs is impeded by three core technical
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relevant to the proposed PhD project (inc. computing, mathematics, engineering etc.). Enthusiasm for research, the ability to think and work independently, excellent analytical skills and strong verbal and
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such as, but not limited to, chemical, pharmaceutical, biochemical, or mechanical engineering; pharmaceutical sciences; materials science; or related areas. Applicants from computer science with relevant
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, and control tissues across phylogenetically diverse Corydoradinae species. Test evolutionary mechanisms by quantifying the roles of gene duplication (including whole-genome duplication), positive
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mechanics, and analytical and numerical methods to solve partial differential equations. Excellent oral and written communication skills. Prior experience in computational fluid dynamics or active matter will
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and AMR markers. By integrating plasmonic signal amplification using gold nanostars with a power-free electrokinetic focusing mechanism, the device will enable early-stage detection without the need
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Institute, with close ties to the Department of Computer Science and Technology. Preferred skills/knowledge We are seeking a passionate and collaborative PhD student with a strong background in machine
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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
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Research theme: Textiles and Apparel How to apply: uom.link/pgr-apply-2425 UK students This 3.5-year PhD studentship is open to Home (UK) applicants and EU students with settled status