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across the U.S. Gulf Coast. EGRET employs an integrated model–experiment (ModEx) approach accelerated by artificial intelligence (AI) to advance predictive understanding of how plant–microbial–soil
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traits, plant-microbe-soil interactions, physical and chemical soil properties, and organo-mineral associations. This candidate will directly support the Exploring Gulf Region Ecosystem Transitions (EGRET
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-institutional collaboration focused on disturbance-driven ecosystem transitions and their impacts across the United States Gulf Coast. EGRET employs an integrated model–experiment (ModEx) approach accelerated by
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five-year mission of the ORNL Quantum Science Center (QSC) to establish a quantum-accelerated computing ecosystem for scientific applications. The successful candidate will develop, test, and evaluate
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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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) at Oak Ridge National Laboratory (ORNL). CSED focuses on transdisciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and
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solutions to compelling problems in energy and security. We are seeking an outstanding Postdoctoral Research Associate with a strong background in condensed-matter physics and materials science – especially
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National Laboratory (ORNL). You will work at the MDF to advance digital manufacturing technologies and to accelerate their deployment to industry and national scale applications. The MDF hosts a diverse set
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computing (HPC), with an emphasis on developing intelligent systems that can accelerate large-scale scientific research on leadership-class supercomputers. The successful candidate will contribute to research
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systems (proteins, enzymes, membranes, and complexes) Integrate AI/ML approaches with physics-based simulations to accelerate discovery and improve predictive fidelity Contribute to cross-scale modeling