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such models, and working with a team of scientists interested in pushing the boundary of predictability. Position Requirements Recent or soon-to-be-completed PhD (completed within the last 0-5 years) in
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The Energy Systems and Infrastructure Assessment Division at Argonne National Laboratory is seeking a highly motivated Postdoctoral Appointee to support research on AI-enabled monitoring, control
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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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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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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to develop and
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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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operando experiments under electrical, thermal, or mechanical bias to capture real-time defect dynamics. Integrate multimodal datasets and collaborate with AI/ML teams for data fusion, physics-informed model
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research will involve synergetic collaborations with a multi-disciplinary team involving engine modelers, CFD experts, and computational scientists to enhance the predictive capability for next-generation
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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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specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors