109 affective-computing-"https:" "https:" "https:" "UCL" Postdoctoral positions at University of Oxford
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for applications is 12.00 noon on Friday 06 March 2026. Informal enquiries may be addressed to Professor Harrison Steel: Harrison.steel@eng.ox.ac.uk Further information can be found at http://www.eng.ox.ac.uk/jobs
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details of two referees as part of your online application. see the University pages on the application process at https://www.jobs.ox.ac.uk/application-process The closing date for applications is 12.00
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criteria found in the job description, and why you would like to do this role. See guidance at https://www.jobs.ox.ac.uk/cv-and-supporting-statement. Any technical questions related to this vacancy can be
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highly automated workflows to investigate the functional impact of germline and somatic mutations in cells and tissues. A central goal of the role is to design experimental and computational pipelines
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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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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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poorly understood. It is also unclear how the conformational landscape of dynein-2 is affected by disease-causing mutations. This project involves using a multi-scale structural biology approach, involving
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The Qing Laboratory at Oxford is seeking a highly motivated postdoctoral researcher to join a NERC-funded Pushing the Frontiers of Environmental Science programme focused on advancing nanopore
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The Qing Laboratory at Oxford is recruiting postdoctoral researchers (multiple positions available) to join a Bill & Melinda Gates Foundation–funded programme focused on developing innovative
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undertake high-impact research at the interface of materials science, advanced imaging, and artificial intelligence, with a particular focus on developing automated approaches for analysing multi-modal