651 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in United Kingdom
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for applicants with a degree in Computer Science, Mathematics, Physics, or Engineering. Prior experience in AI is necessary. Prior experience in tomographic imaging and medical physics would be advantageous but
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the professional, ethical, organisational and work-related challenges surrounding the adoption of AI technology for human selection and evaluation. The research is expected to adopt an interpretivist, social
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second class UK honours degree or equivalent in a related discipline. This project would suit students with an aerospace or mechanical engineering background. Experience of computational fluid dynamics
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Funded PhD Studentship in applied geospatial ecology. This project will investigate how dryland vegetation productivity varies across space and time and how it responds to land management. Working with NEOM, one of the world’s largest ecological restoration programmes, the project will develop...
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scintillators to X-rays and gamma rays using radioisotopes and X-ray generators. The student will be registered on the Physics PhD program; however, the nature of this research project is highly multi
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environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs
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: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in implementation of fusion
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in a relevant subject – Biomedical Sciences, Biomedical/Information Engineering, Computer Science, Analytical Bioscience, Physics or related disciplines. Prior experience with medical imaging
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Are you an outstanding and ambitious engineering or computer science graduate looking for the next challenge? Do you want to work at the frontier of artificial intelligence and robotics to enable
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workflows and contribute to building UK capability in an important advanced reactor area. The ideal candidate will enjoy computational modelling and quantitative problem‑solving, with a strong foundation in