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Supervisor’s full name & email address Dr Yixue Shen: Y.Shen1@leeds.ac.uk Co-supervisor name & email address Professor Christine Unterhitzenberger: C.Unterhitzenberger@leeds.ac.uk Project summary Artificial
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seven renowned professors, and within a Business School that is committed to collegiality and academic citizenship. The posts are open to colleagues with different marketing specialisms, but we
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computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the research will be the inclusion stochastic elements
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of Film, Culture and Society at UCL and secondary supervision by Professor Matthew J Smith at UCL (LBS/Department of History). The student will participate in the Research Training programme and will have
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create a working framework that includes both experimental and modelling prototypes, including AI/ML tools to assist with the large number of variables involved. This project is seeking candidates with a
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or computational modelling is desirable but not essential; applicants should demonstrate strong academic performance, resilience in the face of research challenges, a proactive attitude to learning and a willingness
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background and an interest and expertise in physical, computational and/or analytical chemistry. Please note that this is a 4-year Graduate Teaching Assistant (GTA) studentship, with a slightly higher teaching
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This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
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Funding Source: Warwick Industrial Fellowship (WIF) in partnership with Hydrograph Eligibility: UK only Supervisors: Professor Tony McNally, Dr Fengzai Tang Supporting Company: Hydrograph (see Home
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This PhD programme of work, supported by HTC Health LTD in collaboration with Manchester Metropolitan University, aims to explore the multi-organ communication pathways of the gut, specifically