22 programming-"Multiple"-"U"-"Prof"-"O.P"-"U.S"-"University-of-Bradford" Postdoctoral positions in United Kingdom
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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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predictive analysis for Novartis Oxford collaboration for AI in medicine. The collaboration focuses on improving our understanding of multiple sclerosis disease progression and how treatment can impact
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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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and skills. Good communication skills and travels to other partners across European Union are also required. Main duties will involve in sub-project management and co-ordinating multiple aspects of work
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Application Deadline 16 Nov 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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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