323 data-"https:"-"https:"-"https:"-"https:"-"New-York-University" Postdoctoral positions in United Kingdom
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on delivering high-quality data and mathematical models to inform the response to emerging veterinary parasitic disease threats and the impacts of global change on disease risk worldwide. The research group sits
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information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/ Only online applications received before midday on Friday 03 April 2026 can be considered. You will be required to upload a
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We invite applications for a Postdoctoral Research Associate in developing AI tools to integrate multimodal health data such as genetics, electronic health records, and molecular measurements in
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, training, and dissemination. Please see the below 'Job Description' for further details on the responsibilities and selection criteria, as well as further information about the university and how to apply
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plasticity would be useful but not essential as training will be provided. Informal enquiries may be addressed to Prof. Ed Tarleton (email: edmund.tarleton @eng.ox.ac.uk) For more information about working at
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vitro cell-based assays. You will possess strong experimental design and data analysis skills, with the ability to independently plan, execute and troubleshoot complex experiments. You will have highly
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critically endangered Southern Resident killer whales. This project will use a unique 50-year dataset on this population, alongside comparative data from other mammalian societies, to understand how and why
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inference beyond human data and across many species, as part of a project focusing on predictive plant breeding. You will collaborate with an international team across the Universities of Edinburgh, Oxford
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reports and grant proposals. You should possess a PhD or DPhil (or near completion of) in Machine Learning or Maths. Informal enquiries may be addressed to jakob@robots.ox.ac.uk For more information about
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-of-the-art genealogy-based statistical inference beyond human data and across many species, as part of a project focusing on predictive plant breeding. You will collaborate with an international team across