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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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devices for processing uranium-bearing and stable isotope compounds. The Mechanical Systems Modeling Group applies first principles and empirical approaches to advance the physics and engineering
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that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance and edge computing; The design of architectures
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regulatory requirements. Experience with conduct of operations or equivalent programs (e.g. DOE O 422.1, NRC licensed facilities, Naval Nuclear Propulsion Program, etc.). Experience with hazardous reactive gas
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components utilized in various enrichment technology systems. Assist in the development of associated procedures and process improvements. Participation in research and development activities associated with
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: The selected candidate will work with technicians, process engineers, quality control engineers, quality assurance staff, supply chain staff, safety & security staff, and project managers to implement plans
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experimental facilities. You will be responsible for developing energy-efficient, physics-aware algorithms designed for distributed learning across both high-performance and edge computing environments. You will
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to the target. These systems typically incorporate PLC, VME, or MicroTCA hardware, all integrated using the Experimental Physics and Industrial Control System (EPICS) framework. In this position, the focus is
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physics, materials science, applied mathematics, computer science, or a related field, and no more than five years of experience beyond PhD. Preferred Qualifications: Background in quantum magnetism
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fundamental mathematical methods and algorithms needed to model complex physical, chemical, engineered and biological systems. ORNL’s computational science research focuses on extreme scale computing and data