459 associate-professor-computer-"https:"-"https:"-"https:"-"https:"-"UCL" PhD positions in United Kingdom
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Field
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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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under the supervision of Dr Mehrdad Vasheghani Farahani from Department of Chemical Engineering, with co-supervision by Professor Ian Kinloch from Department of Materials. The successful candidate will
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infrastructure. The successful candidate will benefit from access to extensive expertise across The University of Manchester in civil engineering, structural engineering, fire engineering, computational modelling
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components of the PhD. Helen Parretti (Norwich Medical School) is a GP, Clinical Associate Professor and obesity specialist with expertise in primary‑care‑based obesity‑management interventions and national
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generated by cattle and their surrounding environment can be analysed to identify patterns associated with behaviour, health status and welfare. The research will involve collecting and analysing sound data
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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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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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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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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