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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission
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altitude could modify the optical or physical properties of cirrus, but we are currently limited by a lack of observational data. This project will fill that gap, using existing aircraft and satellite
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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subsequent precipitation hardening process. In addition, promoting a circular economy in the aluminium industry by increasing recyclability and using more recycled aluminium is essential for saving resources
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global warming, but it remains unclear whether it would be effective in practice. CCM relies on the idea that emitting small amounts of aerosols at high altitude could modify the optical or physical
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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strategic priorities: Equality, Diversity and Inclusion (EDI) – We encourage applications promoting and embedding EDI values throughout the whole research process. We also encourage original research
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protocols for electrical biasing of samples in the microscope. A key task is to process and analyse large 4D-STEM data sets and extract information about domain wall structure and dynamics. The role involves