10 programming-"Multiple"-"U"-"O.P"-"FEMTO-ST-institute"-"UCL" Postdoctoral positions at University of Oxford
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with responsibility for technically facilitating the laboratory while academically contributing to multiple large research projects in the topic of the “role of sympathetic neural networks in
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focuses on improving our understanding of multiple sclerosis disease progression and how treatment can impact progression. This work will focus on the unique Novartis Oxford MS (NO.MS) dataset, the largest
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completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying humans and machine learning models. Advanced programming and
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. The post-holder will be one of six centre-funded postdoctoral researchers delivering on projects that form our core research programme. They will be a cornerstone of the centre, collaborating across our
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the universities of Manchester and Oxford. The post-holder will be one of six centre-funded postdoctoral researchers delivering on projects that form our core research programme. They will be a cornerstone of the
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’ programme grant. Find out more about the research and group at: About you Applicants must hold a PhD in Physical Chemistry or a related area, (or be close to completion) prior to taking up the appointment
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surveys, early universe and gravitational physics. Good programming experience, an enthusiasm for coding and data analysis, and the ability to work in a large collaboration, are particularly relevant
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-antigen triggers of regulatory T cells in the context of Multiple Sclerosis (MS). This position is part of a large multidisciplinary collaboration between the University of Oxford, University of Cambridge
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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hepatitis and liver disease. This post is funded by the National Institute for Health and Care Research (NIHR) as part of a significant research programme that leverages large-scale healthcare datasets