65 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at KINGS COLLEGE LONDON in United Kingdom
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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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system may hold clues to how psychosis and other psychiatric disorders are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine
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contributing to multi-site or international collaborative research programmes, particularly in maternal, perinatal, or population health Experience applying machine learning or AI methods in healthcare research
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such as: Systems security, Security engineering, Security testing, Computer forensics, AI for security and privacy, Security and privacy of AI. Our department addresses computer science challenges from a
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environment for the pursuit of cutting-edge cardiovascular and metabolic research (https://www.kcl.ac.uk/scms ). We study the fundamental molecular, cellular, and physiological processes that underly normal and
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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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opportunities and learning and development programmes for health professional researchers. The King’s Clinical Academic Training Office (KCATO) provides research opportunities, champions clinical academic careers
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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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Learning Centre is seeking a Simulation Education Specialist to support the delivery of high-quality, clinically relevant simulation-based education across the Health Faculties. This professional services