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new techniques, most notably protein crystallography, cryo-electron microscopy, DNA sequencing and monoclonal antibodies. The LMB has a clear goal of understanding biological processes at the molecular
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collaboration between the University of Cambridge, SRI International, and more recently Arm, to develop new architectural security primitives. The CHERI protection model embodied in Arm's prototype Morello
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insights into giant planet auroral processes. You will engage in leading-edge research and contribute to high-impact publications, while also representing the research team at national and international
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embedded in the School of Biomedical Engineering & Imaging Sciences, a vibrant community of engineering designing and translating technology into the clinical. The project will follow the King’s College
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breast cancer. In collaborating with cross-functional teams, including bioinformatician, computer scientists, AI engineers, biologists, and clinicians, you will validate AI-generated insights by comparing
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processing and analysis systems for optical and near-infrared mosaic imaging surveys (e.g. VISTA, VST); spectroscopic surveys (e.g. WEAVE, 4MOST); developing pipelines tailored for the analysis of various
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key role in ingesting Bodleian and Oxford colleges’ materials into Digital Bodleian, including images of rare books and manuscripts, maps and modern archival items. You will use online information
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software platforms for electronic healthcare record research and direct care that includes Natural Language Processing / Large Language Model (LLM) capability, e.g. extracting structured information from
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role involves in vivo imaging approaches (e.g. multi-photon microscopy and optical imaging spectroscopy) to assess neuronal and vascular function in the hippocampus and neocortex of awake mice. You will
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principled machine learning approaches inspired by geometry, physics, or domain constraints. Modelling latent representations of complex biological systems or medical imaging (e.g., genomic time series