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the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) to work in the areas of renewable energy and the implementation of such technologies
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to additive manufacturing (AM), virtual manufacturing, material characterization, topology optimization, and real-time sensing. This position resides in the Computational Sciences and Engineering Division (CSED
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, condensed-matter physics, neutron scattering, applied mathematics, and scientific computing. This position resides within the Quantum Sensing and Computing Group in the Computational Sciences and Engineering
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separation science and technologies for energy applications. Support research and program-development activities in advanced separation and purification, including the recovery of critical materials used in
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professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division
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partnerships that advance fiber technology. The role also includes presenting and reporting research results promptly, publishing scientific work in peer-reviewed journals, and sharing findings at scientific
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Requisition Id 16887 Overview: We are seeking a Postdoctoral Research Associate who will support the Ceramics and Ceramics Composites (CCC) Group within the Materials Science and Engineering
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. This position is in the Technology Integration group within NCCS. Specific areas of research interest include: Integration of memory encryption, confidential computing, and trusted execution environments on both
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, technical reports, and presentations. Seek membership and service opportunities in professional, academic, and research organizations. Basic Qualifications: A PhD in computer science/engineering or relevant
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. This position resides in the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL). CSED focuses on transdisciplinary computational science and analytics at scale