34 parallel-computing-"INSERM" Postdoctoral positions at Oak Ridge National Laboratory in United States
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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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computed tomography (XCT) imaging of a variety of specimen types including irradiated fuel samples, analyzing the generated 3D XCT datasets to identify and quantify features of interest, and interacting with
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breeding blankets, including computational fluid dynamic (CFD), thermal hydraulic, and magnetohydrodynamic (MHD) analyses. We seek individuals with advanced analytical and computational skills who can use
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Requisition Id 15217 Overview: The Multiscale Biomedical Systems group in the Advanced Computing in Health (ACH) section in Computational Sciences and Engineering Division (CSED), Computing and
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science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
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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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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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, 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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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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, transportation, and more, with a special emphasis on grid resilience assessments and equity analysis. You will have the opportunity to creatively use interdisciplinary methods from computational data science