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cutting-edge big/deep data analysis methods, including machine learning and artificial intelligence. The ideal candidate will therefore have a strong background in data science and in the application and
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-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
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of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real robots
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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create
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-precision vertexing and tracking of charged particles. Past and current projects include the upgrades of the Inner Tracking System (ITS) for the ALICE experiment at the Large Hadron Collider (LHC) at CERN
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, and advanced data analysis. This role is part of a large-scale, multi-institutional consortium study aimed at uncovering novel insights into the genetic and molecular underpinnings of neurodevelopmental
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influences within Florida's coastal watersheds. Your work will involve integrating GIS mapping, water quality modeling, and environmental data to assess hydrology and water quality dynamics. This position
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a
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management tools. This role involves designing and executing large-scale epidemiological studies using EHR data, overseeing clinical data annotation/processing from public and Hospital Authority sources, and