115 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" positions at King's College London
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well as Machine Learning (ML) tools — to interrogate a very large sample of Electronic Health Records from people with epilepsy across multiple NHS hospitals. They are expected to have experience working in Data
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THIS VACANCY IS OPEN TO INTERNAL APPLICANTS ONLY About us About King’s Digital Our mission is to provide transformative, high-quality digital education, so students can learn, wherever they are. We
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that includes academic, technical and bioinformatics staff as well as external partners at Exeter, Cardiff, UCL and international biobanks. We are looking for someone with a good undergraduate and/or
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CANDIDATES ONLY About Us The applicant will join the Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. We are a highly collaborative
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sets out the actions that we must take to transform how we teach, how and where our students learn and how we support them during their time with us. King’s Careers & Employability (KC&E) empowers over
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combined with human support. To learn more please visit https://www.kcl.ac.uk/research/embrace About the role The Research Fellow in Digital Health & Data Sciences is focused on the development and
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of knowledge in the subject of Robotics to develop research in the field, e.g., robot design, control and mechatronics; 4. Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T
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publications or conference presentations (either as first-author or as a co-author) Machine learning and/or computational modelling experience Experience with brain network modelling and analysis Experience
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academic staff are organised across 7 Science Schools plus the Centre for Education. For more information please see the Faculty’s webpages: https://www.kcl.ac.uk/lsm/index About SUSTech SUSTech is a public
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Familiarity with immune profiling and systems immunology in infectious diseases or critical illness, including sepsis Experience with machine learning approaches for biomedical datasets Planning and preparation