290 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "St" positions at Oak Ridge National Laboratory
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such as drawings, reports, specifications, and studies Develop and apply an understanding of industry codes and standard practices Document work performed in the forms of work instructions, drawings, and
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-on construction of mission equipment Prepare basic engineering calculations following standard methods and principles used in similar engineering analysis. Utilize and develop an understanding of industry codes and
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: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000
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the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws. About ORNL: As a U.S. Department of Energy (DOE) Office of
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Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. Benefits at ORNL: As a U.S. Department
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test and participation in an ongoing random drug testing program. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy
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: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000
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that strengthen U.S. competitiveness in emerging industries. University of Tennessee - Oak Ridge Innovation Institute (utorii.com) . UT-ORII’s overall goal is to become a center for convergent research and talent
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program Visa Sponsorship: Visa sponsorship is not available for this position. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy
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., code interpreters, simulation frameworks, databases, lab instruments) and evaluation for long-horizon tasks. Experience with RL and post-training (reward modeling, preference learning, offline/online RL