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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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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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engagement skills, your interest in the research topic, and future career plans. Full guidance on the application process is available here. Early applications are encouraged. The post is preferred
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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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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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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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: Equality, Diversity and Inclusion (EDI) – We encourage applications promoting and embedding EDI values throughout the whole research process. We also encourage original research addressing key EDI-related
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Dr. Lucy Vanes (lucy.vanes@kcl.ac.uk ) for more information regarding the project and studentship. If you have any queries regarding the application process, please contact the Education support team