319 phd-computer-science-fully-funded-"IMPRS-ML"-"IMPRS-ML" positions at University of London
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independently and in close collaboration with in-country partners. The applicant should have an excellent academic track record that includes formal training in microbiology as well as a relevant PhD (public
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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 delivering professional services within
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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 delivering professional services within
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-Raman spectroscopy (AF-Raman) for intra-operative assessment of sentinel lymph node biopsies in breast cancer surgery' led by Prof. Ioan Notingher (Nottingham) and funded by the National Institute
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in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. The Baby Ubuntu programme is a group-participatory programme
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funded by UK Research and Innovation (UKRI), this programme is part of the government’s strategic effort to position the UK at the forefront of global AI expertise. Our goal is to train PhD researchers
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About the Role We are looking for a Teaching Fellow in Skills/Language for Science and Engineering to undertake a fixed term 2-year post in the Queen Mary Engineering School, in Xi’an, China to
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CoSector CoSector – University of London is a digital services provider that operates as part of the University of London. It evolved from the University of London Computer Centre (ULCC), established in 1968
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View All Vacancies Pathobiology & Population Sciences Location: Hawkshead (nr Potters Bar, Herts) Salary: £35,311 to £40,528 Per Annum Including London Weighting Fixed Term / Full Time Closing Date
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve