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to pathogenicity in the gut, directly addressing mechanisms that underpin susceptibility to fungal infection. You will be based at the Quadram Institute Bioscience and supervised by Professor Alessia Buscaino
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) programme. The post holder will work closely with Professor Ronita Bardhan and contribute to a high-impact, interdisciplinary research programme focused on advancing evidence-based urban design for population
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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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- See advert for details Deadline: 13 April 2026 Supervisors: Dr Zhenhui Yuan and Professor Joseph Hardwicke Predictive Network Intelligence for Medical Telerobotics Research area and project description
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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