501 computer-programmer-"https:"-"Prof" "https:" "https:" "https:" "https:" "https:" "UNIV" positions at University of Oxford
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high-quality code for data preparation and data analysis using commonly used computer languages carrying out descriptive data work including visualisations/plotting preparing and documenting meetings and
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our multidisciplinary team working at the interface of epidemiology, data science, and public health policy. The successful candidate will develop and apply advanced mathematical and computational
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robust risk management across the portfolio. You will bring extensive experience in programme, project and portfolio management within complex organisations. You will have a proven track record in
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application of AI and machine learning models to interpret complex X-ray datasets, and the integration of experimental and computational insights to generate actionable knowledge that advances sustainable metal
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supervision and research leadership for postdoctoral fellows, doctoral and Master’s-level students; the ability to play a major part in developing the Faculty’s research and teaching programme, including
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. The post-holder will be one of six centre-funded postdoctoral researchers delivering on projects that form our core research programme. They will be a cornerstone of the centre, collaborating across our
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physiological systems and disease. The main duties of this post will be to undertake discovery science, secure external funding to prosecute an independent research programme and educate undergraduate and post
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About the role The Department of Social Policy and Intervention is seeking a Research Assistant with computer science and Earth observation expertise to support climate and population data
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term time, weekends, school holidays and potentially some Bank Holidays, depending on programme delivery requirements. Due to the nature of this post, the successful candidate will be required
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and impactful research into intrinsic motivation, with a particular focus on building computational theories that predict human behaviour in the absence of extrinsic rewards, and testing them using