14 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" research jobs at KINGS COLLEGE LONDON
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with Dr. Li and in collaboration with national and international interdisciplinary partners based at the UK Health Security Agency (UKHSA), University of Cambridge, Imperial College London, and John
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with Dr. Li and in collaboration with national and international interdisciplinary partners based at the UK Health Security Agency (UKHSA), University of Cambridge, Imperial College London, and John
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with Dr. Li and in collaboration with national and international interdisciplinary partners based at the UK Health Security Agency (UKHSA), University of Cambridge, Imperial College London, John Hopkins
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with Dr. Li and in collaboration with national and international interdisciplinary partners based at the UK Health Security Agency (UKHSA), University of Cambridge, Imperial College London, John Hopkins
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with Dr. Li and in collaboration with national and international interdisciplinary partners based at the UK Health Security Agency (UKHSA), University of Cambridge, Imperial College London, and John
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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
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establishing a strong academic track record. You may have worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research. Essential criteria PhD
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(Pharmacy, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and
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: david.jackson@kcl.ac.uk Where to apply Website https://www.timeshighereducation.com/unijobs/listing/406107/research-assistant/… Requirements Additional Information Work Location(s) Number of offers
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methodological training courses and attend international conferences alongside opportunities to publish peer-reviewed articles, contribute to the teaching and learning programmes in the department, and gain