207 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" research jobs at University of Oxford in United Kingdom
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for real-time human data processing in interactive settings. Technical expertise in areas such as electrophysiological recording, VR paradigm design, closed-loop algorithm development, or clinical
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, utilising big data, developing digital health interventions and working internationally. We have methodological expertise in clinical trial design and implementation, clinical decision making and diagnostics
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and should also clearly describe how you meet each of the selection criteria listed in the job description. Click here for information and advice on writing an effective Supporting Statement. To discuss
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where information or research material is restricted • Contribute to the design of research materials and make arrangements for data gathering • Gather, analyse, and present
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literature reviews, writing up the results for publication in peer-reviewed journals, and gathering, analysing and presenting data from a variety of sources. The ideal candidate must hold a first degree
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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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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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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