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research and teaching expertise in the related areas; (b) preferably have at least two years of postdoctoral research experience; (c) have demonstrated promise of a high level of creative ability in
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Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric...
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related discipline. Strong background/skills on machine learning, mathematics, probabilistic modelling and optimisation are preferred. To apply please contact the supervisor, Dr Mu - Tingting.Mu
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This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We...
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mathematics is essential. Prior experience with simulation tools or microstructural modelling is desirable. To apply, please contact the supervisor, Prof Andrey Jivkov - andrey.jivkov@manchester.ac.uk . Please
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) culture. This five-year project is led by Professor Sujit Sivasundaram. The successful applicant will join a team of researchers, including postdoctoral fellows and an existing doctoral student
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) culture. This five-year project is led by Professor Sujit Sivasundaram. The successful applicant will join a team of researchers, including postdoctoral fellows and an existing doctoral student
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, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Strong background/skills on machine learning, mathematics, probabilistic
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-time Entry requirements The standard minimum entry requirement is 2:1 (Hons) in physics, chemistry, natural sciences, mathematics, computing, environmental sciences, or similar numerical subject. Start