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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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research programme at Oxford. Candidates should hold a PhD in biomedical engineering, computer science, medical physics, statistics, or a related field. A strong track record of first-/senior or co-author
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(first supervisor), working with Dr David Watson (Department of Informatics). This position is funded by King’s Climate and Sustainability. The key responsibilities of the role are to develop machine
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Computer Science, Optical Communication Engineering, or related field. Candidates at the PDRA level must have a PhD Degree in Computer Science, Optical Communication Engineering, or related topics. Applicants should
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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symposia. These are your qualifications: Must-haves: You have completed a doctoral/PhD degree in Computer Science, Business Informatics, or a closely related field, whereby knowledge of computer science is
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. About you You must hold (or be close to completion of) a relevant PhD/DPhil, together with relevant experience, and posses sufficient specialist knowledge in the discipline. You should be able to conduct
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to artificial intelligence (AI) (e.g. computer science, engineering, Statistics, and mathematics etc.) The post is available for 30 months, starting on 1 September 2025. If you are still awaiting your PhD to be
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have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field such as computational social science, computer science, or cognitive science. They will have a demonstrable track