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, while simulations are subject to error due to uncertainty in nuclear data and unresolved physical processes e.g. thermal expansion and fine-scale inhomogeneities. Generating independent simulation
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sits at the cutting edge of materials science and solid mechanics, using real-world microstructure data to simulate thermo-mechanical behaviour at the grain scale. Your work will form a key part of a
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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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skills. Main duties will include: conduct tissue-mechanical and imaging experiments using early avian embryos; acquire and process data; prepare reagents and samples; optimise protocols; program and debug
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-based reviews, data collection and analysis, written outputs, and the dissemination of research findings to different audiences, including through investor briefings and academic publications. We
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, antennas, and electromagnetic metasurfaces. The computer-aided simulation of electromagnetic fields is critical in the design of most computing and communications devices, such as high-speed interconnects in
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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-edge advancements in automated drug discovery through the integration of high data-density reaction/bioanalysis techniques, organic synthesis, laboratory automation & robotics and machine learning
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and clinical phenotype information. Using these datasets, you will undertake comprehensive strategies aimed at the characterisation and therapeutic targeting of medulloblastoma biology, focussing