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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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in ORNL’s Center for Radiation Protection Knowledge (CRPK). The candidate will work with experts in computational radiation dosimetry and risk assessment. The candidate should be an independent thinker
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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Requisition Id 15815 Overview: The Workflows and Ecosystem Services (WES) group under the Advanced Technology Section (ATS) of the National Center for Computational Sciences (NCCS) is seeking a
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across diverse clients. You will use Frontier's computational power to scale and validate these privacy-preserving algorithms, enabling breakthroughs across energy and image modeling domains. You will also
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national security, proliferation detection, and nuclear forensics applications. This position resides in the Collection Science and Engineering Group in the Material Characterization and Modeling Section
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strategic analysis and modeling research activities of advanced materials, supply chain, and advanced manufacturing technologies for various DOE program offices. The latest analyses focus on DOE’s Advanced
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Requisition Id 15604 Overview: The National Center for Computational Sciences (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral research associate in High-Performance
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the development of AI architecture for holistic genomic photosynthesis modeling. Evaluate performances of AI genomic photosynthesis models. Report advances to program management and broader scientific communities
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modeling techniques and make fundamental contributions to the field. Interact with other researchers, technicians, and students to shape and drive the research agenda. Present and report research results and