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learning, computational neuroscience, and cognitive science, and the student will work closely with both supervisors to move between these perspectives. We are looking for a candidate with a strong
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Rolls-Royce University Technology Centre (UTC) in Manufacturing and On-Wing Technology The growing field of soft robotics has unlocked new possibilities for robotic systems to navigate uncertain and
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engineering excellence needed for the aerospace sector. In this PhD, high-fidelity two-phase Computational Fluid Dynamics (CFD) methods will be used to model complex and fundamental cryogenic hydrogen flows
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This exciting opportunity is based within the Advanced Materials Research Group at Faculty of Engineering to conduct cutting edge research into upgrading novel biomass feedstocks with industrial
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, robotics, and machine learning. You will work within a multidisciplinary supervisory team spanning engineering, robotics, and computer science, and collaborate with researchers working on real-world
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Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career
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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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Group Reps to enhance the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access
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Location: Mechanical and Aerospace Systems Research Group, Faculty of Engineering, University of Nottingham Funding: UK Home fees + tax-free stipend of £24,000 p.a. for 4 years Applications
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after