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:38183983) using cutting-edge genomics technologies (https://www.biorxiv.org/content/10.1101/2024.12.20.629444v5) to provide core knowledge for development of new therapies and management strategies for PPK
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within theoretical physics, including knowledge of quantum field theory, effective field theory and gravitational waves. They should be enthusiastic about contributing to the continuing development
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displacement and return (UNREST). This postdoctoral position will be based at Oxford’s Department of International Development (ODID), and is one of two UNREST research and innovation associateships (RIAs) based
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to the preparation and development of research grant proposals, supporting the group's strong track record of successful funding and helping to expand its research portfolio in explainable and trustworthy AI
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in vivo models to replicate disease. We are particularly interested in the effects of exercise on the development of bone lesions, and the potential role played by mechanosensitive osteocyte cells in
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:38183983) using cutting-edge genomics technologies (https://www.biorxiv.org/content/10.1101/2024.12.20.629444v5 ) to provide core knowledge for development of new therapies and management strategies for PPK
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, Networks, or other related areas, and be proficient in software development and systems administration. The successful applicant will be integrated in a rapidly growing research environment and collaborate
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deliverables. To support the development of further high-quality research proposals. To undertake such other duties as may be reasonably requested and that are commensurate with the nature and grade of the post
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in silico models to replicate disease. We are particularly interested in the effects of exercise on the development of bone lesions, and the potential role played by mechanosensitive osteocyte cells in
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in secure environments Background in medical image analysis (CT/MRI preferred) Knowledge of detection, segmentation, and model development methods Interest in multimodal or longitudinal clinical data