36 phd-position-in-information-retrieval Postdoctoral positions at University of London
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In Vitro Predictive Models to Explore Tendinopathy”. The project is funded by the Medical Research Council (MRC) and part of the organ-chip research work underway within the Centre for Predictive in
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scheme Potential applicants wishing to discuss this position informally are encouraged to contact Dr Isabel Orriss by email (iorriss@rvc.ac.uk) We promote equality of opportunity and diversity within
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the School/Department/Institute/Project The Wolfson Institute of Population Health (WIPH) is an exciting and dynamic environment, home to 400 staff, 91 PhD students and more than 500 postgraduate taught
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collaborative and interdisciplinary and the ability to work in a team is essential. About You The successful candidate will be expected to have a PhD degree in biological or computational sciences or equivalent
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populations using patient samples and employing a combination of multi-modal techniques (scRNA-seq, scATAC-seq, ResolveOME) to develop novel assays for disease monitoring. The post is based at the Barts Cancer
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***INTERNAL APPLICATIONS ONLY*** About the Role A position is available for a Postdoctoral Research Associate to join the laboratory of Silvia Marino in the Brain Tumour Research Centre
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have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
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dynamic strain and flow fields during flight. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. Desirable competencies would include
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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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research aims to optimise personalised treatment approaches for atrial fibrillation patients by using long-term therapy outcomes across populations of patients to inform patient-specific predictive