190 software-verification-computer-science Postdoctoral positions at University of Oxford
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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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choice theory, or computational modelling. This post is based at the Department of Computer Science and on-site working is required. Remote and part-time working is possible in agreement with Professor
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learning, at the intersection of reinforcement learning, deep learning and computer vision, in order to train effective robotic agents in simulation. You should hold a relevant PhD/DPhil (or near completion
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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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at the University of Oxford and work collaboratively with academic partners at Warwick, Berkeley, Potsdam, Groningen and beyond. This post is based at the Department of Computer Science and on-site working is
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Nuffield Postdoctoral Research Fellowships Grade: 07 RS, salary: from £48,235 to £52,539 per annum The Department of Economics, in partnership with Nuffield College, is offering full-time
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Wellcome Trust and by project-specific funding from the EU Horizon programme. As part of a multi-disciplinary research team, you will contribute to analyses of the global food system. Some of the interests
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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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, calcium imaging, optogenetics and/or behavioural methods. The project is part of a broader research programme designed to use cross-species research to uncover mechanisms for memory in both health and
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Materials & Composites Laboratory: https://eng.ox.ac.uk/mmclab/) in the Department of Engineering Science at Oxford University. The post is funded by the ERC Proof-of-Concept (PoC) grant: RESILIENT and is