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Field
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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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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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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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Postdoctoral Research Scholar in Machine Learning and Computational Genomics Department of Epidemiology, School of Public Health, University of Pittsburgh The Department of Epidemiology
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per annum. This is inclusive of a pensionable Oxford University Weighting of £1,730 per year. We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep
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qualifications: PhD or equivalent achievement (proof of independent research capability) in Machine Learning, Computer Science, Physics, Mathematics, or a related field Deep theoretical knowledge and extensive
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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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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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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