89 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "The Institute for Data" positions at KINGS COLLEGE LONDON
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education. For more information about the School, please see our website: https://www.kcl.ac.uk/politics-economics About the role The School of Politics and Economics are seeking a hard-working, enthusiastic
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, providing unique opportunities for students and staff. Link to IoPPN webpage: http://www.kcl.ac.uk/ioppn/index.aspx About the role: This is an exciting opportunity for a Lecturer in Health Psychology
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recognised scientists and clinicians from across the School and King’s College London. More information: https://www.kcl.ac.uk/scmms About The Role This is an exciting opportunity for a Postdoctoral Research
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Date: 01-Feb-2026 Contact Person: Professor Michael Simpson Contact Details: Michael.simpson@kcl.ac.uk Where to apply Website https://www.timeshighereducation.com/unijobs/listing/405602/academic-position
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communities in London; Fostering global citizens with an international perspective. Find out more here - https://www.kcl.ac.uk/about About The Role We are looking for an exceptional Senior Philanthropy
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, 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 research
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design, control and mechatronics; Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T-RO, CVPR, ICML; Excellent verbal and written communication skills, including academic
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, 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 research
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About us: We are seeking to appoint a postdoctoral research associate with an excellent track record in semantic technologies and machine learning. Topics of interest in this area include, but
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are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine-learning to identify the treatment-relevant immune processes, with an emphasis