30 machine-learning-and-image-processing Fellowship positions at University of London in United Kingdom
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Surgery, in the Department of Clinical Science and Services. You will be expected to enhance the department’s reputation through scholarship in clinical activities and teaching. You will achieve this by
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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning techniques, and
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, including seeking opportunities for mutual learning and training. The successful applicant will have a track record of relevant research experience, excellent communication skills, and an ability to work both
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have a postgraduate degree, ideally a doctoral degree, in a relevant field and experience in computer-based analyses and presentation of experimental data. The successful applicant would have a proven
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doctoral degree, in sexual and reproductive health or a relevant subject/discipline and a recognised teaching qualification equivalent to the LSHTM Postgraduate Certificate in Learning and Teaching, or to be
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by the automated system until 10pm of the closing date. Any queries regarding the application process may be addressed to jobs@lshtm.ac.uk . Please quote reference EPH-NCDE-2025-13. The supporting
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at LSHTM. Applications should be made on-line via our jobs website . Online applications will be accepted by the automated system until 10pm of the closing date. Any queries regarding the application process
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jobs website . Online applications will be accepted by the automated system until 10pm of the closing date. Any queries regarding the application process may be addressed to jobs@lshtm.ac.uk . Please
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queries regarding the application process may be addressed to jobs@lshtm.ac.uk . Please quote reference EPH-NCDE-2025-11. The supporting statement section should set out how your qualifications, experience