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(or ability to obtain one) preferred. Preferred Experience Familiarity with AI security, adversarial machine learning, or cyber-physical systems. Experience working with or within federal agencies such as DoD
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measurement activities to evaluate the mechanical and thermophysical properties of irradiated materials. Acquire, process, analyze, and report test data in accordance with applicable manuals, procedures, and
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, collaboration, inclusion and continuous learning. Stakeholder Engagement & Partnerships: Serve as the external interface for the center: liaise with sponsors (DOE, other federal agencies, industry, academia
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optical systems, thermal imaging, pyrometry, spectroscopy, high speed imaging or acoustic sensing. Familiarity with data analytics, machine learning, or signal processing. Knowledge of metal additive
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analytics that enhance and evolve business operations and scientific decision-making capability and related activities at ORNL.Qualified applicants will have a solid foundation of Generative AI and Machine
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the development, implementation, and interpretation of optical plasma diagnostics and integration of real-time data acquisition systems. Experience with machine learning and data-driven approaches to diagnostic
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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response to upset conditions in the data centers. Operators are trained to the Computational Science Building Computer Center Operations Emergency Response Plan and Emergency Response Checklists. Upset
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technical environment. Strong programming skills in production controls, full-stack, or related experience. Proficiency in relational databases and data governance. Proficiency in Machine Learning techniques