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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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phenomena Create new reduced-order models and submodels related to fluid flow, heat transfer, thermochemistry, and electrochemistry in reactive systems Use modeling tools such as computational fluid dynamics
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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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The Center for Energy, Environmental, and Economic Systems Assessment (CEEESA) works on innovative research to enhance the resilience, efficiency, and affordability of power grids. Advanced
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The Multiphysics Computations Section at Argonne National Laboratory is seeking to hire a postdoctoral appointee for performing high-fidelity scale-resolving computational fluid dynamics (CFD
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The Computational Science Division (CPS) at Argonne National Laboratory (near Chicago, USA) is seeking a postdoctoral researcher to enable exascale atomistic simulations of ferroelectric devices
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(completed within the last 5 years or nearing completion in 2026). Proven ability to conduct independent research or technical development, analyze complex systems, and publish results or deploy production
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://arxiv.org/abs/2509.00098 ) This project sits at the intersection of artificial intelligence and materials characterization and modeling. The goal is to create an AI system that can intelligently operate
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of Large Language Models (LLMs) for scientific use cases. This position focuses on advancing LLM capabilities to address complex challenges across a range of scientific domains. As part of a
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range of molecular systems, including: Transition-metal complexes (e.g., chiral ruthenium and iridium complexes) Local and nonlocal inner-shell decay processes in solvated ions and transition-metal