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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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be expected to be willing to learn new skills and train others. The SNS and HFIR facilities are in operation 24 hours per day and 7 days a week year-round. You may be occasionally required to support
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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Learning skills. This position resides in the AI Operations Program office within the Application Development Division of the Information Technology Services Directorate. Our AI/ML models are heavily
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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