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sold network with aerospace sector which help the students in the result discussions This is a self-funded PhD open to UK, EU and international applicants. Research carried out during this PhD project
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to industrial clients such as Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD, Bombardier, QinetiQ, Thales, Network Rail, Schlumberger and Alstom. Entry requirements A minimum of a 2:1 first degree in a
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funding restrictions, this is only available to those eligible for UK fees. How to apply: All applications should be made online . Under programme name, select School of Sport Exercise and Health Sciences
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Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission
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computational recourses for limited duration yet highly accurate particle-in-cell (PIC) modelling. Kingston University has developed a simulation model, dubbed PERSEUS, that narrows the gap between these two
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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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, nanofabrication, and computational electromagnetism. Strong coding (Python /MATLAB) and experimental aptitude is desirable.
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programme. Details of how to apply for the PhD programme are available at this page: https://www.sheffield.ac.uk/postgraduate/phd . When you apply, you should include the supporting documents relevant
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
evidence-based interventions in elite sport environments. The successful candidate will be integrated in a programme of research involving the continuous collection of physiological and behavioural data via