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. In this role, you will leverage large-scale, heterogeneous datasets to develop and deploy AI-driven methods for: Real-time quality monitoring and control of manufacturing processes Understanding
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to additive manufacturing (AM), virtual manufacturing, material characterization, topology optimization, and real-time sensing. This position resides in the Computational Sciences and Engineering Division (CSED
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professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division
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Division (MSTD) at Oak Ridge National Laboratory (ORNL), and who will focus on ORNL's continued development of methods to quantify shear (yield) strength of monolithic ceramic materials as a function of
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advanced manufacturing processes. This position resides in the Deposition Science and Technology Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak
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the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) to work in the areas of renewable energy and the implementation of such technologies
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the Materials Engineering Group within the Large Scale Structure Section, Neutron Scattering Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL). The selected candidate will work in a
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Requisition Id 16798 Overview: The Data and AI Systems Research Section/Workflow systems Group within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is
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maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment. About ORNL: As a U.S. Department of Energy (DOE) Office of
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with the world's first exascale system, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate