343 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" "UCL" positions at Oak Ridge National Laboratory
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, decommissioning of systems and components Maintain experimental data and logbook records related to enrichment operations. Support the development and review of procedures, instructions, reports, presentations, and
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, decommissioning of systems and components Maintain experimental data and log book records related to enrichment operations. Support the development and review of procedures, instructions, reports, presentations
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objectives into robust pipelines, automate job orchestration and data movement, and optimize end-to-end workflow performance on large-scale Linux-based HPC environments and hybrid cloud/HPC platforms. Job
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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 of addressing the nation’s
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funded by the U.S. Department of Energy (DOE) Office of Basic Energy Sciences (BES) in the Materials Sciences and Technology Division (MSTD). The successful candidate will be expected to work effectively
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ferroelectric and ferroelastic materials, under external stimuli such as electric fields, light, strain, and temperature. This position resides in the Data Nanonanalytics (DNA) Group within the Nanomaterials
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challenges and conduct the research needed to accelerate the delivery of solutions to the marketplace. The Radiation Transport and HPC Methods (RTHPCM) Group within the Nuclear Applications Methods and Data
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Requisition Id 16186 Overview: The National Center for Computational Sciences (NCCS) at Oak Ridge National Lab (ORNL), which hosts several of the world’s most powerful computer systems, is seeking
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troubleshooting skills down to board level. General computer skills (e.g. using menu and software driven test equipment). Experience installing, maintaining, inspecting, diagnosing, and repairing electrical systems
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physiologists, and data scientists to tackle fundamental issues in AI/ML-based photosynthesis research and applications. The selected scientist will have access to the world’s most advanced resources in computing