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supercomputer, the world's first exascale computing system. This is a unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and
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optimization and consensus algorithms. Knowledge of large models and hyper-parameter optimization. Knowledge of high-performance computing and its applications. An excellent record of productive and creative
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Technology Computational Group facilitates ORNL goals through HPC systems engineering, integration, and support for the research community at ORNL. By providing design, deployment, optimization, monitoring
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Requisition Id 16824 Overview: The Multiphysics Modeling and Flows (MMF) Group in the Computational Sciences and Engineering Division is seeking a Research Computational Scientist with expertise in
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the development and optimization of products for a variety of industries from automotive to aerospace made from new bio- and waste-derived plastic resins and fillers. The ideal candidate for this role would be
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stakeholders on system capabilities, best practices, and optimization opportunities. Basic Qualifications: BS/BA degree in Information Systems, Human Resources, Business, Computer Science, or related field, and
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on diverse technical environments. High-performance computing (HPC) specialization such as cluster management, parallel computing, and performance optimization. Hardware and software: The ability to deploy
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communities. You will work closely with a focused group of scientists, technicians, and engineers on challenging, fast paced technical projects in support of the DOE Isotope Program. This has been a quickly
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. Optimize system and component designs for performance and safety. Develop agentic workflows for scientific computing. Author peer-reviewed papers, technical reports for internal and external release and
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: Develop, maintain, and optimize LabVIEW-based software for data acquisition, monitoring, and control applications across new and existing systems. Lead the design, integration, and deployment of real-time