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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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control) the arrangements of cells in spheroids and tumoroids. The project will primarily involve the development and testing of machine learning techniques based on biophysical simulations to predict
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), research is carried out in computer vision, robotics and machine learning. We are now looking for two postdocs in robotics and machine learning and computer vision. The successful candidates is expected
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Job related to staff position within a Research Infrastructure? No Offer Description Join a transformative project at RIBES using machine learning and genomics to overcome linkage drag and accelerate
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Are you inspired by the quest for new materials for solar cells, spintronics, and quantum technologies—and eager to accelerate their discovery with machine learning and materials theory? Are you
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technologies—and eager to accelerate their discovery with machine learning and materials theory? Are you passionate about linking atomistic processes to device performance through computer simulations? Are you
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at RIBES using machine learning and genomics to overcome linkage drag and accelerate crop breeding by design. You will build models, analyse new sequencing data and optimise strategies for combining
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Postdocs in Generative Machine Learning for Biomedical Data. The postholders will focus on developing and applying state-of-the-art generative models (such as VAEs, GANs, and transformer-based architectures
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Old Road Campus, Headington, Oxford, OX3 7LF 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...
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related discipline. Strong expertise in medical imaging and/or machine learning. Excellent programming and research skills. Interest in translational research and interdisciplinary collaboration with