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) and Computational Fluid Dynamics (CFD), for polymer composite manufacturing processes Perform multi-physics simulations involving coupled thermal, mechanical, and material behavior across multiple
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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. Publish high-quality, impactful, peer-reviewed journal articles and reports. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork
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security challenges facing the nation. ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of
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pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and
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radioisotopes, conduct transformative R&D in isotope production and separation, reduce U.S. dependence on foreign isotope sources, and strengthen domestic supply chains for national economic resilience. This call
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of open literature publications in these areas. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote
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APPFL and OmniFed. Major Duties and Responsibilities: Conduct and publish original research focused on data readiness methodologies and frameworks for scalable AI applications across fluid dynamics
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perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Basic Qualifications: A PhD
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computing. Redesign of storage systems to meet evolving demands in AI/ML and edge-to-HPC workflows, including support for data movement, retention policies, and user-defined storage behaviors. Major Duties