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biology in atherosclerosis. The project will combine patient-derived endothelial colony-forming cells with advanced coronary artery imaging from patients at Barts Health NHS Trust to identify individuals
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collaborative programme bringing together a team of leading experts in advanced electron microscopy imaging, first-principles modelling, metal halide semiconductor thin-film and device fabrication, and
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culture models and cell imaging to decipher mechanisms contributing to cancer cell invasion. We offer a vibrant and creative multidisciplinary environment, and the successful candidate will be supported
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. About You You will have, or be close to completion of a PhD/DPhil in Statistics, Machine Learning, Data Science, or a related quantitative discipline. You will demonstrate strong specialist knowledge in
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and forward-looking environment in which colleagues can develop their careers and contribute to shaping the future of computer The Role The role focuses on advancing research in explainable and
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bioinformatics. The role will be responsible for developing and characterising human dorsal root ganglia cultures to benchmark the newly developed iPSC derived organoid model systems. This will include processing
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spectroscopic tools (photoelectron imaging and action spectroscopy) to study the structure and dynamics of transition metal complexes. The research project aims to develop a new method for elucidating
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schools, doctoral supervision, and software outputs central to the Centre’s mission. About You You will have, or be close to completion of, a PhD/DPhil in Statistics, Machine Learning, Data Science, or a
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into the regulation and function of diverse cellular processes. To this end, we use Vaccinia virus as a model together with quantitative imaging and biochemical approaches to study a variety of cellular processes
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, sequencing, automation, imaging, and bioprocessing. GBI will also have access to substantial compute resources that can be leveraged to further accelerate progress, including scientific compute, bioinformatics