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to a project at the interface of research, policy, and international collaboration. The PDRA will gain experience in managing a complex bilateral programme, authoring outputs with direct policy impact
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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Application Deadline 23 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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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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previous GEM initiatives, including the Inclusive Cities programme. You will have a passion both for academic research and for knowledge exchange with policy makers, NGOs, and other stakeholders and an
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collaboration. The PDRA will gain experience in managing a complex bilateral programme, authoring outputs with direct policy impact, and strengthening partnerships that will continue well beyond the funding
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Location: Old Road Campus Research Building, Headington, Oxford, OX3 7DQ We are seeking five full-time Postdoctoral Research Assistants to join the Computational Health Informatics Lab
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We are seeking five full-time Postdoctoral Research Assistants to join the Computational Health Informatics Lab at the Department of Engineering Science, based at the Institute of Biomedical
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The Royal Veterinary College, University of London; | Potters Bar, England | United Kingdom | 20 days ago
). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural dynamics simulations to recover dynamic strain and flow fields