76 evolution "https:" "https:" "https:" "https:" "https:" positions at University of Oxford
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for candidates to pursue an independent research programme in applied mathematics, and to join a large existing cohort of leading researchers on Fellowship programmes at the Mathematical Institute: https
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, and developing ideas for generating research income. You will supervise and mentor students and research staff, providing guidance on methods, analysis, and career development, and represent the Centre
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governance of the college. They will also be expected to contribute to the department’s research portfolio in Chemical or Biochemical engineering, obtaining external funding to enable development of a new and
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developing ideas for generating research income. You will supervise and mentor students and research staff, providing guidance on methods, analysis, and career development. You will also conduct cutting-edge
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biomedical image analysis or computational psychology. You will have proven experience in stochastic analysis and neural differential equations and with the development of stable diffusion models. Post
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sustainability to pioneering healthcare solutions - and join a diverse, inclusive community that champions your wellbeing, development, and aspirations. Apply now to become part of our extraordinary legacy
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Collaboration. The primary focus of this post will be the development of computational pipelines for the automated extraction and discovery of image-derived phenotypes (IDPs) across multiple imaging modalities
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, Diversity and Inclusion Committee (EDI Committee). We will invest in your personal development through training and professional development. You will lead The School of Geography and the Environment’s
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-on leadership. You will also play a key role in shaping the future scientific direction of the group and supporting future grant development. About the Radcliffe Department of Medicine The Radcliffe Department
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and artificial intelligence. This role offers a unique opportunity to support the development and evaluation of a multi-agent Retrieval-Augmented Generation system designed to accelerate understanding