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reactions. We welcome applicants from diverse backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate
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about exploring and applying new statistical, computational, or machine learning techniques to astronomical data sets, and extending current methodology to be applicable in the era of big data. Looking
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Description Conduct a part of the ANR MetaTime (setting-up experiments, acquisition and processing of data, writing scientific reports) • Perform a review of the existing litterature on the topics • Acquire
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Neurobiologie (ZMNH) Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI (baiome.org) to complement our lively and enthusiastic team of machine learning and
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of the areas listed on the page above are of interest to you. The list includes positions covering Operator Algebras, Machine Learning, Analytic Number Theory, Automorphic Forms and Representation Theory
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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equations, uncertainty quantification, and machine learning. Candidates must have obtained a Ph.D. in mathematics or applied mathematics before the start date and must demonstrate research excellence, strong
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acquisition and management. This role directly builds upon Ph.D. research by applying advanced 3D imaging, algorithm design, machine learning, software engineering and visualization techniques to a real-world
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shoulders up to 25 pounds. Standing and sitting at computer terminals and laboratory bench completing repetitive tasks for extensive periods of time. Continuous working with materials requiring personal
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Standing or sitting up to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Some flexibility, generally Monday- Friday, 8-5 Job Summary This position is designed to have 60-70 percent