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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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simulation and flood inundation modeling. River basin planning and operations modeling, including reservoir simulation and optimization. Hydrodynamic modeling of water temperature and quality constituents
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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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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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seeking to fill a Postdoctoral Research Associate position to work in the areas of environmental life cycle assessment (LCA), technoeconomic optimization; and industrial energy efficiency and production
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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. Implement and optimize data representations and pipelines suitable for machine learning and uncertainty quantification. Collaborate with AI/ML experts to design and test inference methods that map
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developing the technical basis for the first fusion nuclear facility and the position will involve several disciplines, with an intended focus on design, analysis, and optimization of fluid flows in tritium
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. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, industrial engineering
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a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD degree in physics or related discipline completed within the last five years