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Laboratory (ORNL). As part of our research team, you will closely collaborate with a team that includes condensed matter theorists, experts in neutron/X-ray scattering, and experts in thin film and single
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Postdoctoral Research Associate - Theory-in-the-loop of Autonomous Experiments for Materials-by-Desi
carlo), as well as experience in developing and/or applying advanced AI/ML methods to accelerate materials discovery. The project will involve integrating such theory-informed AI-models for creating
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
length/time scales, to provide improved mechanistic insights into nanomaterials response. Bulk of the work will be on novel materials for next-generation microelectronic devices (e.g. oxide ferroelectrics
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. Related fields, including hydropower and power grid modeling, hydraulic engineering, and sediment transport. The successful candidates must demonstrate an ability to work independently, evidenced by
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strong background in quantum computing, computational physics, and a solid understanding of condensed matter quantum many-body theory. This position resides within the Quantum Computational Science group
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Requisition Id 15537 Overview: We are seeking a Postdoctoral Research associate in computational nuclear physics. This position focuses on nuclear theory with an emphasis on nuclear structure and
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and nuclear structure and reactions. The position is part of the nuclear theory team that resides in the Theoretical and Computational Physics group in the Physics Division, Physical Sciences
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develop cutting-edge differential privacy techniques for large-scale models across multiple institutions. This position offers a unique opportunity to work with the world's first exascale system
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Requisition Id 16020 Overview: We are seeking a Postdoctoral Research Associate to reside within the Sample Environment and Labs Section, which is part of the Neutron Scattering Division (NSD
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL