215 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at KINGS COLLEGE LONDON in United Kingdom
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning
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Details: informatics-hod@kcl.ac.uk Where to apply Website https://www.timeshighereducation.com/unijobs/listing/404894/reader-in-computer-… Requirements Additional Information Work Location(s) Number
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About us The Department of Informatics is looking to appoint a Reader in Computer Vision Education. This is an exciting time to join us as we continue to grow our department and realise our vision
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level. Successful candidates will teach and supervise students who are serving officers and civil servants in the UK and allied armed forces and partners. There are also opportunities to contribute
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. The Centre has expertise in International Education and makes a significant contribution to the rich and diverse make-up of the King’s student body. About the role The Learning Technology Officer will support
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renowned for its innovative teaching and cutting-edge research. Our iTEL Hub supports the integration of digital education and technology-enhanced learning (TEL) across the faculty and collaborates with
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Shrivenham and will undertake high-quality scholarship and support a range of professional military and security education courses at the postgraduate level. Successful candidates will teach and supervise
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of Mental Health & Psychological Sciences, and our NHS and industry partners. We particularly welcome candidates whose expertise complements existing departmental strengths in machine learning, multimodal
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complements existing departmental strengths in machine learning, multimodal data integration, digital phenotyping, and trial emulation using electronic health records. This is a full-time post (35 hours per
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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge