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This project is a fully funded MSc by Research Scholarship in Medicinal Chemistry / Synthetic Organic Chemistry and builds on a successful decade-long research programme at the University of Exeter
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Proposed topic “Creating a National Digital Twin for self-harming
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: At least an upper second-class degree (preferably MSc) in a Science or Technology discipline. Good working knowledge of machine learning and deep learning. Hands-on knowledge of Python or PyTorch
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expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a multidisciplinary team at KCL, UCL and with clinicians
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capture, evaluate the potential apportionment of soil/sediment chemistry to sources and locations from established field experimental plots and catchments-valleys identified from baseline data using isotope
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King's College London Department of Engineering | London, England | United Kingdom | about 1 month ago
. You will be part of an active research programme in the Heat and Fire Lab (https://heatandfire.github.io/ ) in the Department of Engineering under the supervision of Dr Francesco Restuccia . Our group
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is critical for a wide variety of engineering and environmental applications, remains unexplored. You will join a team of researchers that experimentally quantify the flow-physics of fundamental
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to validate computational fluid dynamics modelling to determine drag and vortex-induced vibrations on dSPCs associated with biofouling. Better understanding of the hydrodynamic consequences on dSPCs from key
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Sciences at the University of Exeter’s Cornwall campus, home of the internationally recognised Environment and Sustainability Institute. Local government and civic society groups in Cornwall will offer a
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farms at relatively close proximity can be relevant when considering their annual energy production. This project will examine the uncertainty of various types of numerical models, from fast-computing