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the Department of Energy and the State of Tennessee. More About the Workflow Systems Group: The Workflow Systems Group researches and develops systems and algorithms to enable knowledge discovery from scientific
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transport problems across the fission and fusion energy fields. These areas include application of cutting-edge high performance computing algorithms, workflows, and methods to solve problems related
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, Hugging Face etc., in applied problem-solving contexts. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers
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discovery with a strong emphasis on domain-driven impact. Develop, optimize, and transition algorithm prototypes to robust implementations Work with ORNL researchers, as well as internal and external project
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conditions, identification of vulnerabilities, and development of resilience enhancement strategies. Contribute to the design, development, and implementation of new models, methods, and algorithms
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partnerships with industry, universities, and other national laboratories Design and implement advanced sensing and controls algorithms for manufacturing Communicate research results through presentations
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algorithms. An understanding of when to apply what data-driven approach, from statistical techniques to generative AI models. Experience working with DOE National Laboratories (or similar R&D organizations
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advanced sensing and controls algorithms for manufacturing Communicate research results through presentations, reports, conference papers, and peer-reviewed journals Deliver ORNL’s mission by aligning
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validate these distributed intelligence algorithms, enabling breakthroughs in scientific research across DOE domains. The candidate will collaborate with DOE’s SWARM project (https://swarm-workflows.org
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algorithms and techniques for advanced manufacturing applications. The group consists of highly talented experts in image/signal processing, mechanical engineering, data analytics including artificial