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transcription factors contain long disordered regions, but an incomplete understanding of their roles impedes transcription factor and therapeutics design. You will describe roles quantitatively by biophysically
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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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transmission at multiple scales’, working with researchers at the Universities of Manchester and Cambridge, and the London School of Hygiene and Tropical Medicine. The project will involve the analysis of whole
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detailed T-cell phenotyping and functional assays • Conduct mechanistic studies using molecular and cellular immunology techniques • Contribute to data analysis, presentation, and publication
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member of the ‘Blackholistic’ team (Oxford-Amsterdam-Radboud) which includes relativistic simulations on all scales from black hole to large scale jets, as well as analysis of data from the Event Horizon
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including conditional diffusion and flow matching models for synthesising Magnetic Resonance Imaging (MRI) and predictive analysis for Novartis Oxford collaboration for AI in medicine. The collaboration
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a social science discipline (or a relevant data science field), have interest and research in the field of economic and experience in data management and analysis. You have demonstrable experience
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analysis. The engineering targets identified using computational approaches by the successful applicant will be validated in crop plants by other members of the consortium. This is an exciting collaborative
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applicant should have prior experience in data analysis, data visualization, and preferably the development of interactive web-applications through approaches such as Bokeh, Shiny, Taipy, Streamlit etc
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and analysis. You will be expected to manage your own academic research and administrative activities. This involves small scale project management, to co-ordinate multiple aspects of work to meet