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through papers, artifacts, and presentations at top-tier venues. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, a physical/computational science discipline (e.g., physics, chemistry
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process-based modeling of hydrologic or land surface processes. The WSMG group develops advanced surface/subsurface integrated hydrologic and reactive transport models, works with other groups to compare
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and machine-learning-driven optimization frameworks for polymer composite manufacturing processes. This position resides in the Composites Innovation Group in the Manufacturing Science Division (MSD
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, finite volume, and machine learning to solve challenging real-world problems related to structural materials and advanced manufacturing processes. The successful candidate will have experience with
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in Computer
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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD degree in Computer Science or a related discipline. A strong background in scientific data
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environment consisting of mathematicians, computational and computer scientists, and domain scientists conducting basic and applied research in support of ORNL’s mission. Specific responsibilities include
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Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD