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London, with a team of investigators covering AI, computer vision, robotics, and medical imaging. You will join a dynamic and successful team with access to both cutting-edge computer power and advanced
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and implementing vision processing algorithms that enable robust robot tracking and autonomy. The ideal candidate will possess hands-on experience designing, implementing, and deploying computer vision
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detection models, with a focus on achieving generalisable multimodal understanding in zero-shot settings. About You The successful candidate must have a PhD (or equivalent) in the field of computer vision or
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Postdoctoral Research Assistant in Design for Behaviour Change: Circular Economy for Medical Devices
contribute to the strategic vision and long-term planning of Oxford’s research in technical AI governance. You should possess a PhD/DPhil in machine learning, computer science, engineering, or a closely
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the delivery of the 3-year EPSRC Funded ‘Digitally Enabled Circular Healthcare Innovation’ (DECHI) research programme. The aim of the programme is to investigate how advances in digital technologies and digital
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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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United Kingdom Application Deadline 9 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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United Kingdom Application Deadline 9 Oct 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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assessments. Competence in data analysis and databased management, including techniques relevant to longitudinal studies (e.g. mixed models, SEM, in R, Stata, MPlus, or other suitable programme) Proven ability
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(e.g. mixed models, SEM, in R, Stata, MPlus, or other suitable programme) Proven ability to report research findings with clarity and rigor, demonstrated through authorship of peer-reviewed publications