627 parallel-and-distributed-computing-phd positions at University of Oxford in United Kingdom
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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, reporting to Prof. Mauro Pasta. Applicants must hold PhD/DPhil in Materials Science or Chemistry (or be close to completion), together with relevant experience in the field of beyond Li-ion batteries, in
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posters locally and at national and international conferences, as well as participate in MRC grant’s research programme led by Prof Marco Fritzsche. You must hold a relevant PhD/DPhil (or be near completion
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. For candidates interested in research beyond the current post, there may be opportunities available to develop a programme towards a higher degree (PhD) in an associated topic. You will be working in a growing
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contribute to the preparation of research reports and funding proposals, and may assist in coordinating aspects of this complex, multi-institutional research programme. With a current PhD/DPhil (or close to
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dissemination and grant writing. About you You will hold a PhD (or be close to completion) in a relevant field, in addition to experience of implementing or fine-tuning LLMs using machine learning libraries
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and politicians and you will be handling this material with appropriate care. This is a permanent part-time post, working 21.9 hours per week, either three days a week or distributed over several days
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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the delivery of the departmental masters programme. The successful applicant will have a relevant PhD or DPhil with post-qualification teaching and research experience, sufficient depth and breadth
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programme focused on deciphering the molecular architecture of the HLA antigen processing and editing machinery, and investigating how it shapes tumour-specific antigen presentation. Your project will focus