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computational scientists, economists, engineers, and other researchers to develop data-driven, decision-relevant analytical tools for complex industrial systems. Key Responsibilities: Develop, improve, and apply
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evaluate advanced algorithms for applications such as secure and adaptive control, anomaly and attack detection, resilient decision-making, and AI-enabled operational support for highly distributed grids
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-driven modeling (including ML/AI where appropriate) to help anticipate vulnerabilities and inform decision-making for energy deployment and national competitiveness. In this role you will : Conduct and
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, performance, and reliability for scientific applications. Develop and deploy autonomous LLM agents capable of reasoning, planning, and decision-making to support complex scientific workflows. Implement
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performance. The candidate is expected to publish results in refereed journals and make oral presentations at meetings conferences, symposia, and seminars. The candidate is expected to maintain cognizance
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Argonne National Laboratory, a U.S. Department of Energy national laboratory located near Chicago, Illinois, has an opening for a highly motivated postdoctoral appointee in the Decision and
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The Energy Systems and Infrastructure Assessment (ESIA) division provides the rationale for decision makers to improve energy efficiency. We develop and use analytic tools to help the U.S. achieve
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will be part of a dynamic team working collaboratively with researchers in Q-NEXT (both at Argonne and other academic and industrial member institutions), and is expected to build on and create new
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. The division aims to build lab-wide cross-cutting simulation application capabilities integrating with mathematics, computer science, domain science, and advanced computing architectures and facilities