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infrastructure and digital hardware systems. This position is part of the Controls Integration Group in the Control Systems Section in the Research Accelerator Division of the Neutron Sciences Directorate at Oak
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on Accelerating Fusion Technology and as an ORNL UT-ORII staff fellow, successful applicants will be part of a team of Research Faculty and ORNL staff to collaborate in the area of Fusion Materials. In this role
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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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for the design and analysis of computational methods that accelerate data analytics and machine learning, especially as the apply to scalable high-performance computing, cloud computing, and large interconnected