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rupture, which is one cause of a stroke and thus the prediction of plaque rupture is very relevant. The steps in the development of surrogate models are building data-driven models from medical imaging
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number variations, are major risk factors for adverse mental health outcomes. Beyond their clinical importance, they provide powerful human models for uncovering multiscale genetic mechanisms in psychiatry
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framework capable of accurately predicting pollutant transport and dispersion in coastal waters. By combining high-fidelity numerical simulations with data driven surrogate models, the proposed research aims
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experiments, behavioral research, econometric and causal inference approaches, optimization and analytical modeling, and data-driven techniques such as machine learning and large language models. Our work is
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IMPACT can be found here: https://more.bham.ac.uk/impact/ IMPACT is led from the University of Birmingham, with multiple partners across the UK. Stirling is the lead Scottish HE partner and the role is