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Requisition Id 16720 Overview: Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security. The Environmental Sciences Division of...
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, and data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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Requisition Id 16779 Overview: We are accepting applications for Postdoctoral Research Associate positions in Data Science for Advanced Manufacturing that will focus on the development of next
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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Requisition Id 16798 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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signature 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
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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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work with multidisciplinary teams to develop, validate, and demonstrate advanced mobility technologies using large-scale transportation data, high-fidelity simulation, vehicle-in-the-loop testing
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ecosystem processes. The position offers the opportunity to work at the interface of model development, observational data synthesis, and emerging AI/ML methods, in close collaboration with researchers from
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workflows for grid modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The