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- KINGS COLLEGE LONDON
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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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 measurements to determine whether aircraft exhaust is
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programme’ page, please select (Neuroimaging) Research MPhil/PhD (Full-time). More information on the department and the programme is available at the departmental prospectus page here: https://www.kcl.ac.uk
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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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are looking for: A PhD (or have submitted your thesis before taking up the role) in Materials, Physics, Chemistry or a closely allied discipline Expertise in 4D-STEM data acquisition Expertise in cryogenic
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The role The post is part of the Wellcome Discovery Award research programme “Collective Action for Race Equity in Health and Social Care”, which aims to address and dismantle structural factors
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Requirements We will only consider candidates with a good Bachelor’s degree (ideally, a first, minimum 2:1) and/or a master’s degree in computer science, data analytics, health economics, or computational
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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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biology, and biochemistry. Plan, conduct, and contribute to experimental work. Identify and develop relevant methods for data collection, analysis, and interpretation. Develop expertise across scientific