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tools, collaboration with project stakeholders, and engagement with the consortium and Defence and Security stakeholders. Technical Requirements: Strong coding skills with background in machine learning
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for a team player with exceptional communication skills who is enthusiastic about developing cutting-edge cardiotherapies whilst also supporting undergraduate and postgraduate student learning through
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will a have a relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning
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in statistics, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded
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funding and contribute to the process of securing funds and make presentations at conferences and other events. Applicants will possess a relevant PhD or equivalent qualification/experience in a related
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engineering science, with knowledge and/or some experience of energy technology and policy; and/or quantitative analysis including econometrics, statistics and machine learning and related disciplines handling
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medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and astrostatistics. These posts
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. The researcher would be expected to have knowledge of protein structure, protein ligand binding, machine learning and expertise in workflow development. Information generated by the project will be widely
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to) fundamental research in machine learning or statistics, algorithm design, the application of AI methods in science, healthcare, social sciences, or business. You should have a PhD or equivalent level of
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Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate