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About the Role Applications are invited for a post-doctoral research associate to lead on a Barts Charity funded project. The research involves application of machine learning methods to heart and
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About the Role The overall objective of the project is to develop a reduced-order surrogate model for predicting the ammonia direct injection spray characteristics using hybrid machine learning
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We are looking to appoint a research scientist to carry out research in machine learning and artificial intelligence to develop interpretable clinical decision support tools and novel methodologies
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both machine learning and symbolic AI. The discovery of new solid electrolytes is a core project target. You will have a PhD in Chemistry, Physics or Materials Science. The post is available from 1st
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: machine learning, applied topology, and/or probability theory. About the School The School has an exceptionally strong research presence across the spectrum of Mathematical Sciences. It is part of
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and esteemed industrial and governmental partners. Your expertise in machine learning, statistical analysis and programming will drive impactful research aimed at solving real-world challenges. Why join
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. This data will help shape paediatric-specific T2T endpoints and facilitate the development of personalized treatment strategies. You will apply advanced statistical and machine learning methods, and your
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the risk of many diseases, including developmental disorders and cancer. In this role, you will work on the development of statistical models and machine learning algorithms and their application to large
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of experts in machine learning and colour vision, including Dr Alexandros Koliousis (NU London), Professor Rhea T. Eskew (NU Boston), and Professor Andrew Stockman (UCL), as well as with technical
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. We have wide-ranging interests in data science and machine learning, and in numerical modelling, theory and observations of key applied mathematics areas to make breakthroughs in our understanding