29 assistant-and-professor-and-computer-and-science-and-data Postdoctoral positions at University of London in United-States
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Computer Science or a related topic. Applicants at the PDRA level must have a PhD in NLP or machine learning. Substantial knowledge of Natural Language Processing (NLP) and machine learning methods is essential, as
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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adoption, maternity and paternity pay and leave. Prospective applicants are encouraged to contact Professor Kristien Verheyen by email: kverheyen@rvc.ac.uk For further information and to apply online please
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View All Vacancies Comparative Biomedical Sciences Location: Hawkshead (nr Potters Bar, Herts) Salary: £40,528 to £51,470 Per Annum Including London Weighting Fixed Term / Full Time Closing Date
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developmental science. The successful candidate will contribute to a major research programme investigating how educational experiences shape mental health from childhood into adulthood. The role involves working
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Technology Laboratory (DSTL), Electromagnetic Environment (EME) Hub. About You Applicants should have a PhD in modelling hypothetical scenarios, with and without data, for structured decision-making under
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About the Role A 12 month post-doctoral research assistant position funded by the Barts and the London Charity (BTLC) is available in the laboratory of the laboratory of Professor Stuart McDonald
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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will deliver projects that leverage large-scale electronic health record data and rich cytometry data derived from full blood count analysers to develop and refine machine learning models to improved