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, specialises in laser-matter interactions of metal additive manufacturing, and the co-supervisor, Professor Paul Mativenga (UoM), has extensive expertise in laser materials processing. Dr Chu Lun Alex Leung
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of involved phases. Candidate requirements You must have very good knowledge and expertise in material physics and/or chemistry or computational solid-state physics/ chemistry Candidates with experience in
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be compared and calibrated. In-silico technique based on Computational Fluid Dynamics (CFD) will also be developed to provide further information necessary for the development of new MRI image scanning
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motivated and ambitious PhD candidate skilled in genetic epidemiology, biostatistics, mathematics computational biology or related discipline to contribute to the “Hereditary & Early onset breast cancer
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applied knowledge of qualitative research methodologies, including qualitative interviewing, ethnography, and document analysis. However, when joining the KBS PhD programme the student will receive support
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Supervisors: Dr Negar Gilani and Professor Richard Hague The Centre for Additive Manufacturing (CfAM) Research Group within the Faculty of Engineering at the University of Nottingham, recognised as
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autonomous systems. Supervision The project will be supervised by Dr Anthony Siming Chen (EEE), with co-supervision from Professor David Branson III (M3) and Professor Praminda Caleb-Solly (Computer
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Professor Dirk vom Lehn and Dr Juan Baeza (King’s Business School, PSMO) as well as by Michael Bowen (College of Optometrists). Collaboration The studentship is supported by the Research and Knowledge
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status rate at the School of Mechanical, Aerospace and Civil Engineering at the University of Sheffield under the supervision of Professor Pierre Ricco (www.pierre-ricco.co.uk ). Additionally, the student
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About the project: Supervisor: Professor Nicholas Hine, University of Warwick This project uses cutting-edge computational and machine learning methods to accelerate catalyst discovery for fuel cell