1,030 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" research jobs in United Kingdom
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the Light Microscopy Facility (https://www.sheffield.ac.uk/lmf). Wild-type and mutant lines will be crossed to transgenic lines of interest for live fluorescence imaging. There will also be the opportunity
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to the 30th September 2026. We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics
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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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supporting better patient outcomes. The successful candidate will lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning
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lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP
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, University of Oxford. This is a 24-month, fixed-term position, funded by the Simons Foundation. The start-date for this position is flexible, but September-November 2026 is preferred. The project will focus
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machine learning model to rule out heart attacks in the emergency room, which has the potential to translate to large savings for healthcare systems in the world, (2) a computational modelling to assist in
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degrees in psychology. Our pre-covid NSS scores for overall satisfaction was above 90% for eight years and since covid have been ahead of the sector average and sector benchmarks. We provide a learning
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the requisite experience. Desirable: B1 An awarded (or recently submitted or near completion) PhD in subject specialism or equivalent. B2 Experience with high dimensional statistical, machine learning and deep
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’. The role-holder will work closely with medicinal chemists at University of Oxford and pharmacologists at University of Glasgow, applying virtual screening, machine learning, AI-driven generative chemistry