11 machine-learning-phd "The Art Institutes" positions at Medical Research Council in United Kingdom
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machine learning to analyse cardiac motion for predicting patient outcomes, discovering potential therapeutic targets and identifying genetic risk factors. We use a flexible and inter-disciplinary approach
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of a 3-year program using cardiovascular MRI to assess modifiable mechanisms of aging. Applicants should have an established track record of research in machine learning, statistics and bioinformatics
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internationally competitive research programme at the Laboratory of Molecular Biology (LMB) in the area of machine-learning/ artificial intelligence to further our understanding of biology at the molecular and/or
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, facilities and operational staff and PhD students as well as guests to the institute. Main duties: 1. Internal Communications: Keep communications current by managing LMS intranet content, website and social
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staff, facilities and operational staff and PhD students. Other important external stakeholders include Imperial College London, UKRI and MRC as well as many charitable and education partners
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the training of PhD students and other members of the LMB. Key responsibilities: Within the overall direction of the programme, the group, the remit of the project and in discussion with the Group Leader, you
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for publication. • To contribute to the LMB’s mission in the public engagement of science, and the translation of research findings into improvements in health care. • To assist in the training of PhD
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to the LMB’s mission in the public engagement of science, and the translation of research findings into improvements in health care. • To assist in the training of PhD students and other members of the LMB
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Research Support staff, Postdoctoral Scientists and students, not only in your group, but also across the LMB and with external collaborators. Person Specification Academic qualifications and experience: PhD
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will liaise with end users to plan in maintenance works or project works as required. You will be responsible for interrogating the computer-controlled Building Management Systems (BMS) to monitor and