56 environmental-data-science Postdoctoral positions at Oak Ridge National Laboratory
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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Requisition Id 17001 Overview: Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy (DOE) science and energy laboratory, conducting basic and applied research to deliver
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Requisition Id 17078 Overview: We are seeking a Postdoctoral Research Associate to join the Data Science and Engineering for Nonproliferation Group in the National Security Sciences Directorate
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, Chemistry (i.e., Analytical, Physical), or a related field completed within the last 5 years. Demonstrated skills and hands-on experiences with advanced materials characterization equipment and/or data
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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to deliver transformative solutions that advance national energy and security priorities. The Biosciences Division (BSD) within the Biological and Environmental Systems Science Directorate (BESSD) is seeking a
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science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information
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Materials Analysis in the Nuclear Nonproliferation Division in the National Security Sciences Directorate at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop, validate, and extend
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chemistry, specifically x-ray photoelectron spectroscopy. Electrochemistry background, specifically time-resolved impedance. Candidates must show proficiency in developing techniques and data. An excellent
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for geothermal casing related harsh environments applications. A background in polymer chemistry research or related fields, composite material development, material science, and data analysis is preferred. Strong