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algorithms, capable of distributed learning on high performance and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence
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, flexible work environment. Attract a high-quality pool of candidates and hire staff members who are committed to world-class R&D and aspire to be the best in their field. Assist staff in setting performance
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. They will work closely with scientists, technicians, and engineers on technical projects in support of the DOE Isotope Program and other DOE missions. This program offers opportunities for professional growth
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for isotope enrichment. They will work closely with scientists, technicians, and engineers on technical projects in support of the DOE Isotope Program and other DOE missions. This program offers opportunities
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scientific computing, control theory, data science, data driven methods, discrete mathematics, graph algorithms, high-performance computing, integral equations and nonlocal models, linear and multilinear
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Ridge National Laboratory (ORNL) is seeking a staff fellow with expertise in machine learning and high performance computing to help develop high-fidelity computational tools that are used for large-scale
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Performance Computing, particularly queueing and high-speed networking. Strong knowledge of multiple Linux distributions is preferred. Strong knowledge of open-source web application services (Apache, Tomcat
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equipment, facilities, and systems so that they are ESH&Q compliant. Perform all work in a safe manner. A high degree of precision completing activities such as measurements and mixing of chemical solutions
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research workloads, delivering reliable, high-performance object, block, and file storage services. Ensure the availability, performance, scalability, and security of production storage environments
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Documentation: Develop and manage key project artifacts such as charters, roadmaps, software quality assurance plans, and high-level requirements. Oversee Financials: Perform cost-benefit analyses, allocate