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graph neural networks for complex sensor networks such as those involved in brain imaging Develop and test data-driven methods for image and video processing for microendoscopy. Key Duties and
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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sources include traffic emissions, industrial processes, tobacco smoke, and domestic combustion (e.g. poorly ventilated stoves or heaters). While CO at low concentrations acts as a physiological signalling
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research. We study the fundamental molecular, cellular, and physiological processes that underly normal and abnormal cardiovascular and metabolic function and drive the translation of this strong basic
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biological questions about how cytoskeletal proteins are used by disease-relevant organisms. We have access to excellent facilities such as the Central Oxford Structural and Molecular Imaging centre (COSMIC
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developing and applying deep learning models, particularly in areas such as natural language processing (e.g. use of LLMs), computer vision (e.g. CNNs for image classification), and multimodal data integration
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uncover how epithelial cells organise in space and time under different physico-chemical environments to drive self-organisation processes, like condensates, that shape mesoscale structures enabling tissue
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to demonstrate effective and efficient multi-tasking and maintain accurate and up-to-date records. In addition, the applicants should have a high level of proficiency with computer software related to laboratory
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cytoskeletal proteins are used by disease-relevant organisms. We have access to excellent facilities such as the Central Oxford Structural and Molecular Imaging centre (COSMIC), as well as the Micron imaging
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and