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collaborators across institutions to enable integration of scattering-derived insights into physics-informed AI models. Document research results, contribute to publications in peer-reviewed journals, and present
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and lanthanides within controlled atmosphere gloveboxes. Apply chemical thermodynamic and kinetic theories to understand processes and develop models of material interactions and behavior in molten salt
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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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Under the guidance of a supervisor, the Postdoctoral Researcher will conduct research in electrochemical energy storage to support the Battery Performance and Cost (BatPaC) modeling team
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate
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of projects simultaneously. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. This position requires an on-site presence at the Argonne campus in Lemont
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The Postdoctoral Appointee will be part of an R&D group developing multiphysics modeling tools with applications to nuclear fuel recycling, critical materials recovery and purification, and nuclear
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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models for microelectronics materials Curate, manage, and integrate heterogeneous datasets from experiments and simulations Collaborate closely with experimental teams to benchmark and refine computational