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but not essential. A strong background in materials science and/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition
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and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National Physics
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Aviation Education, Training & Research, delivering impactful industrial and academic partnerships, future-proof skills, innovation, and leadership to achieve Net Zero Aviation by 2050. This exciting project
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, this is only available to those eligible for UK fees. All applications should be made online via the above ‘Apply’ button. Under Campus, please select ‘Loughborough’ and select Programme ‘Chemistry’ Please
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and biomaterials research within the Lab. This experimentally focused PhD position will fit a wide range of application interests, suitable for applicants from all engineering and scientific backgrounds
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Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London. The successful candidate will work on developing a novel AI-powered conversational
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Aviation Education, Training & Research, delivering impactful industrial and academic partnerships, future-proof skills, innovation, and leadership to achieve Net Zero Aviation by 2050. This exciting project
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related to the Natural Sciences such as Biology, Conservation, Ecology, Genetics or Environmental Sciences BSc applicants need to demonstrate proof of a level of scientific independence, e.g. having
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PhD Studentship: Revolutionising Litz Wire Development for Next Generation Ultra-High Speed Propulsion Motors The Manufacturing Technology Centre UK, and University of Nottingham This project offers
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3-year PhD studentship: Scaling-Up Functional 3D Printing of Devices and Structures Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD