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statistical mechanical theory. Collaborations with internal and external fusion efforts will be strongly encouraged. The successful candidate will be mentored and teamed with staff in the National Center
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance
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, repair, and calibration of electronic components, equipment, and systems. You will apply principles and theories of electronics to ensure all work is performed in accordance with internal procedures
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. The successful candidate will be a highly motivated and creative problem solver, comfortable working in both the office and the field to satisfy some of the nation’s most complex data collection and processing
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computational foundations of that capability and help bridge the gap between Bayes theory and practical application: knowledge integration, developing robust likelihood frameworks, sampler behavior for long
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Hands on experience in the mechanical testing of metallic materials and associated theory Experience with destructive characterization and identification of metal alloy microstructures and underlying
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National Laboratory (ORNL). This group leads the application of machine and cascade theory to develop, execute, and interpret testing evolutions for discovery, performance evaluation, and optimization
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National Laboratory (ORNL). This group leads the application of machine and cascade theory to develop, execute, and interpret testing evolutions for discovery, performance evaluation, and optimization
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chemistry, radiochemistry, theory, spectroscopy, and materials characterization. This project will develop materials and processing technologies that will result in a transformational improvement in
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related principles, theories, professional competencies. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service