320 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "St" positions at Oak Ridge National Laboratory in United States
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the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once
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technical setting. Familiarity with ORNL processes and systems. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing
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to this position, please email ORNLRecruiting@ornl.gov indicating the job requisition ID number. For technical questions related to this position, contact restrepojm@ornl.gov . About ORNL: As a U.S. Department of
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-227, and Th-228. Located about 25 miles northwest of Knoxville, Tennessee, ORNL is one of the pre-eminent multidisciplinary research facilities in the nation. ORNL is a U.S. DOE laboratory and is
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candidates: If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk
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-227, and Th-228. Located about 25 miles northwest of Knoxville, Tennessee, ORNL is one of the pre-eminent multidisciplinary research facilities in the nation. ORNL is a U.S. DOE laboratory and is
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economic benefits for the nation. Our partnerships with U.S. Department of Energy (DOE) laboratories, universities, and industry enable us to accelerate science and innovation. The Office of Research
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advanced modeling and simulation in support of DOE missions and national priorities. CCSD researchers drive breakthroughs that enable scientific discovery, strengthen national security, and accelerate U.S
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the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once
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that integrate with existing or new large language models and large vision models for resource optimization with energy grid data. Provide coding support to implement privacy preserving federated learning