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About the role We are seeking a Research Assistant to join the INTREPID programme (IN vitro TumouR Explant models for evaluating cancer complexity and Patient Diversity), hosted within the Patient
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required (for a period of 36 months) to conduct research as part of the IGNITE programme, in collaboration with Rolls-Royce, LSN Diffusion and the Universities of Leicester, Sheffield and Warwick. Birmingham
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to broader management/administration processes Contribute to the planning and organising of the research programme and/or specific research project Co-ordinate own work with others to avoid conflict
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Are Looking For We need someone who is comfortable working at the intersection of hardware and software. You will ideally have: A qualification in engineering, computer science, or a related field. Practical
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characterisation programme as a postdoctoral researcher. The ability to think outside the box with creativity, along with having the drive and ambition to develop those ideas in a highly experimental laboratory is
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Research Fellow in Earth System Modelling Salary: Grade 7 (£41,064 – £48,822 p.a. depending on experience) Location: Met Office, Exeter (with scope for hybrid working) Would you like to join a team assessing the main risks associated with global climate change? Would you like to apply your...
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Location: Rex Richards Building, South Parks Road, Oxford OX1 3RQ About the role This post is a postdoctoral research assistant role within Prof Robert House’s Group in the Department of Materials. The post is in association with a new Faraday Institution-funded project entitled “Accelerated...
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. Willingness to learn complex statistical analyses of fMRI data (this might include analysis methods such as multivariate data analysis, machine learning or computational modelling) Desirable CriteriaExperience
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research programme focusing on evidence generation to further methodology research and to enable the design and development of in-vitro diagnostics and medical devices for patients and the NHS. NIHR HRC IVD
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our multidisciplinary team working at the interface of epidemiology, data science, and public health policy. The successful candidate will develop and apply advanced mathematical and computational