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), supernovae, gravitational wave sources, magnetic activity in exoplanets, and machine learning classification. The candidate will lead and participate in observations and data analysis of these sources in all
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exploration and etc. We are seeking distinguished scholars who will teach at UCAS while conducting research at CAS institute platforms—focusing first on over 20 key areas. Early-career scientists worldwide
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physics, nuclear astrophysics, quantum sensing, machine learning, gravitational waves, and particle theory and experiment. Faculty members include Professors Weiping Liu, Jie Chen, Sebastian Garcia-Saenz
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affiliates reflect strengths in machine learning, biological modeling, data ethics, data sovereignty, computer science, environmental data science, climate change policy and modeling, evolutionary genetics
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knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the opportunity to publish novel
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for Contemporary Education in Precision Timing (ACCEPT), faculty across Physics and Astronomy, Electrical and Computer Engineering, Aerospace Engineering and Mechanics, Computer Science, Materials Science, and
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the development of novel research concepts. The scientist will lead Argonne’s Rapid Prototyping Laboratory (RPL), a team of computer scientists, roboticists, data scientists, and subject matter experts
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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the development and implementation of machine learning models Special Physical/Mental Requirements Special Instructions For information on UNC Postdoctoral Benefits and Services click here Quick Link https
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experience in large-scale structure simulations, working knowledge of applications of machine learning techniques in cosmology and/or astrophysics (in particular simulation-based inference), strong programming