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and realign how we measure and model populations by infusing new types of data, methods and unconventional approaches to tackle the most challenging demographic problems of our time. We are seeking a
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cytometry will be an advantage. The project has a major computational component both for AI-driven modelling and predictions, and for bioinformatics analyses of wet-lab data. This will be performed by
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better position. A model is needed into which to feed critical information and retrieve cause/effect insights on which to base logical decisions. Biological information cuts across diagnostic boundaries
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within medical imaging and computational modelling technologies. Our objective is to facilitate research and teaching guided by clinical questions and is aimed at novelty, understanding of physiology and
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science, engineering) and possess experience of developing statistical and computational models using AI. For an informal discussion about the post, please contact Dr Christopher Yau (christopher.yau@wrh.ox.ac.uk
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to projects involving designing, conducting, and disseminating health economic studies using prospective research study or routine data, decision analytic modelling, health outcome assessment methods and other
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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and modelling of nanoelectronic devices operating at cryogenic temperatures (4 Kelvin - 77 Kelvin) for energy efficient quantum computing (QC) and high-performance AI computing in data centres
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)genetic perturbations and mouse in vivo models to investigate the contributions of tissue-specific gene regulation and non-coding GWAS signals to cardiac traits and diseases (Frost et al bioRxiv 2025, Parey
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Computational Methods for Advanced Research to Transform Biomedicine (SMARTbiomed ), an international collaboration that integrates large-scale, multimodal biomedical data with advances in statistical and machine