38 assistant-professor-and-human-computer Postdoctoral positions at Oak Ridge National Laboratory
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division
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testing program. Security, Credentialing, and Eligibility Requirements: For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally
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Requisition Id 15242 Overview: We are seeking a Postdoctoral Research Associate to help advance our understanding of quantum materials through experimental studies of bulk single crystals
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to communicate research results through reports, publications and presentations. Experience in accelerator physics, including working in a control room, conducting accelerator-based experiments, and computational
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chain, material flows, and development costs throughout the lifecycle of a geothermal well to identify opportunities to reduce materials, time, and environmental impact of geothermal wells. Help support
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, industrial energy systems, energy efficiency of manufacturing industry, or other related fields. You will play a crucial role in the planning, execution, and optimization of our technical assistance program
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at the intersection of quantum information science and fundamental materials physics. The research program focuses on understanding the fundamental limits of spin-based quantum sensors as probes of magnetic and
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computations relevant to the development of strategic nuclear performance codes for nuclear reactors. This position resides in the Radiation Effects and Microstructural Analysis Group (REMAG) in the Materials in
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the High Flux Isotope Reactor (HFIR) and the Radiochemical Engineering Development Center (REDC), as you help guide the strategic growth of our isotope production enterprise. This position will primarily
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directly with breeders, conversion laboratories, and genome editing groups to deliver high value genotypes, traits, and sequences. Use and assist with the development of AI-based plant phenotyping