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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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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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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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have or be close the completion of a PhD/Phil in molecular or cell biology or neuroscience or a relevant area together with relevant experience. Experience in mammalian cell culture and analysis
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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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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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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
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statistical programming using R and/or Python, with experience in data management, analysis, and visualisation. You must have demonstrated experience working with large-scale biological datasets, preferably