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take on College officerships, where appropriate. Candidates will have recently completed, or be close to completing, a PhD in a relevant subject. They will have publications in peer-reviewed journals
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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme, focused on understanding and preventing disease progression in
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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project will involve both remote-sensing and field-based observations and data collection. It will provide outputs to the World Bank CAWEP (Central Asia Water Energy Power) programme to aid the design
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students and PhD students. Applicants will have, or be close to completing a PhD in a relevant field and possess relevant experience, in the area of probability or statistical machine learning. They will
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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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Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across
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Calinescu and Prof Doyne Farmer. The postholder will work in the Department of Computer Science at the University of Oxford, based in the Wolfson Building, Parks Road, Oxford. The project is intended
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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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% FTE The successful candidate will hold a Master’s or PhD degree in a Social Science or Science disciplin,e demonstrating strong quantitative data analysis skills. Current PhD students studying part-time