79 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "P" scholarships at University of Nottingham
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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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(School of Medicine), Teaching Associate – thomas.bestwick-stevenson@nottingham.ac.uk This project is not funded, and we are seeking a student who can self-fund the PhD. Programme description: The overall
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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: The overall theme
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Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written and spoken English. Desirable: Experience with photonic/electromagnetics design
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Centre of Excellence. This is a 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
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/Electromagnetics theory, design and simulations Machinelearning mathematics and algorithms Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written
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. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experiences with engineering design, structural/aerodynamic/aeroelasticity modelling, manufacturing/assembly process
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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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for registration with the RCVS or be in the final stages of a veterinary degree programme leading to RCVS eligibility. Informal enquiries may be addressed to the principal supervisor: vicky.strong1@nottingham.ac.uk
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a groundbreaking £6 million EPSRC Programme Grant to reduce the soaring energy demands of artificial intelligence . The computational team will work in collaboration with many partners in academia and