46 data-science Postdoctoral positions at Oak Ridge National Laboratory in United-State
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physics, fusion research, life sciences, and materials science. Furthermore, these efforts to enhance data readiness for AI workflows may play a significant role in contributing to the goals of the 2025
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students and contribute technical expertise to team projects aligned with ORNL’s strategic scientific goals. Basic Qualifications: Ph.D. in Computer Science, Data Science, Computational Science, or a
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Requisition Id 15598 Overview: 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
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capabilities in a wide range of areas, including applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, 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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and instrumentation, controls, data science, and robotics along with close interactions with industry partners. These engagements will play a vital role in ensuring success of programs and the adoption
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and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems in the world. This position is in the Technology
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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems
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scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers, devices, and
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applied mathematics and computer science, experimental computing systems, scalable algorithms and systems, artificial intelligence and machine learning, data management, workflow systems, analysis and