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of Sport, Exercise, and Nutrition Education – kimberley.edwards@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: Athletes, coaches
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
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the organisational and cultural implications for the Probation Service in England and Wales of the expansion of electronic monitoring (EM) and its impact on those subject to supervision. The prison population is at a
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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unique opportunity to work on advanced image analysis and image-driven modelling as part of a wider multi-disciplinary programme that includes mathematical modelling, cancer metabolomics and novel
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Social Statistics Sociology Academic requirements You must meet the minimum academic requirements for your preferred programme Nationality restrictions This funding is available to all nationalities
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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
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we are looking for The candidate should have a 1st or high 2:1 degree in mechanical/aerospace/manufacturing engineering, computer science, physics, mathematics, or related scientific disciplines
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to undertake a programme of doctoral studies (PhD) in a UK university. The Fund was originally set up to promote research in the broadly defined areas of vocational guidance and careers. Applicants
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at the intersection of theory, computation, and high‑fidelity simulation, the successful candidate will contribute to the development of a novel ensemble-based framework for analysing driven perturbations in wall