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analyzing and interpreting experimental data to drive product innovation, as well as obtaining and calibrating simulation parameters based on laboratory results. Regular interfacing between experimental and
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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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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 and storage systems
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with the world's first exascale system, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate
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, characterize physiological impacts, and link genotypes to phenotypes using next‑generation sequencing, systems biology, and complementary analytical approaches. This position requires close collaboration with
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data analytics, and manufacturing process optimization. Develop and apply models, algorithms, or data analysis workflows to support machining process understanding, machine tool characterization, process
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the data science, process analytical technology, and chemical processing domains to address technology challenges for raidoistoope production and application. Major Duties/Rsponsibilities: Perform
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research assignments related to advanced thermal and energy system technologies, including: Conduct experimental and analytical research to evaluate advanced thermal and energy technologies, including energy
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computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage. Proficiency in materials data analytics, including correlation analysis and machine learning techniques. Preferred
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and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems in the world. This position is in the Technology