80 system-science-"https:"-"https:"-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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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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Qualifications: A Ph.D. in Chemistry, Materials Science and Engineering, Mechanical Engineering, Industrial and/or Systems Engineering, Polymer Science and Engineering or a related discipline obtained within
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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
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for this candidate are between two larger efforts in the laboratory. The first effort is in identification of cost-effective technologies (both emerging and at industrial scale) for critical minerals recycling from
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: Familiarity with safety hazards associated with industrial gases Fluency in reading and interpreting process engineering diagrams Developing or working with experimental gas flow systems and gas analysis
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Requisition Id 17130 Overview: The Plant-Soil Interactions Group within the Environmental Sciences Division (ESD) at Oak Ridge National Laboratory (ORNL) seeks a postdoctoral researcher in Coastal
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Requisition Id 17011 Overview: The Nuclear Energy and Fuel Cycle Division (NEFCD) of Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to assist in the development
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Document About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up
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. in Quantum computing, Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a closely related discipline, with demonstrated knowledge of or research experience in
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(ORNL) is seeking a highly motivated Postdoctoral Researcher with expertise in artificial intelligence and machine learning (AI/ML), remote sensing, Earth and environmental sciences, and the analysis