24 component-labeling-agorithm-cuda Postdoctoral positions at Oak Ridge National Laboratory
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computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems. The group is part
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complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM delivers fundamental and applied research
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publication standard Ability to work independently and collaboratively as part of an interdisciplinary research team. Preferred Qualifications: The successful candidate will have research experience in aquatic
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Qualifications: • Experience with error-corrected methods for fault-tolerant quantum computing. • Experience with common quantum programming languages • Ability to work independently and as part of a team
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Postdoctoral Research Associate - Theory-in-the-loop of Autonomous Experiments for Materials-by-Desi
part of our research team, you will be working with a highly interdisciplinary team of scientists at the CNMS, and across other divisions at ORNL. Major Duties/Responsibilities: Work closely with members
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Program (DOE IP) to advance the chemical processing of unique f-element isotopes, including Cf-252, Bk-249, Es-254, Fm-257, and Pm-147. A core focus of the DOE IP is to improve and develop novel chemical
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Sciences and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL). As part of our research team, you will engage with researchers with various backgrounds such as materials science, sensing
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characterization, mechanical testing, 3D microstructural analysis, finite element simulations, atomistic modeling, and thermal transport measurement techniques to advance mechanistic understanding and predictive
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of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and