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another, work together, and measure success. Basic Qualifications: A PhD in chemistry, nuclear chemistry, or a related discipline, completed within the last five years Preferred Qualifications: Candidates
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Requisition Id 16798 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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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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) advanced cooling solutions for energy systems; (3) thermal management for electronics and data centers; and (4) separation processes for building environments. Develop experimental setup, problem-solving
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biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and
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will design and implement differential privacy solutions for large-scale scientific data models in federated learning environments. You will advance privacy-preserving machine learning by developing
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modeling, optimal power flow (OPF), surrogate modeling, and data-driven analysis of large-scale electric power system simulations on DOE leadership-class computing resources. The candidate is expected
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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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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in materials science and engineering, physics, chemistry, electrical engineering, or a
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-efficient building systems, thermal-fluid processes, industrial heating applications, data center thermal management, and other emerging energy technologies. Develop and operate experimental facilities