137 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"University-of-Chester" Postdoctoral positions in United Kingdom
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Oxford Population Health (the Nuffield Department of Population Health) provides an excellent environment for multi-disciplinary research and teaching and for professional and support staff. We work together to answer some of the most important questions about the causes, prevention and...
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background knowledge in statistical genetics, machine learning, omics data analysis, and computational biology. Additional knowledge in transcriptomics, statistics, and foundation models is also desired. Fixed
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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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, cardiovascular diseases and rare diseases. This specific role focuses on engineering CAR-T cells and developing programmable gene control systems to improve safety and therapeutic efficacy. The successful
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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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Aalto University is inviting applications for a Postdoctoral researcher in molecular machine learning. The successful applicant will join the research group of Professor Juho Rousu. The position
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The Department of Statistics is recruiting to a Florence Nightingale Bicentenary Fellow in Statistical Machine Learning. This is career development positions intended to carry around half the
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that integrate multi-omics data to uncover mechanisms of disease, cellular resilience, and therapeutic response. The post holder will lead research applying large-scale machine learning and foundation models
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fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC