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successful candidate will conduct research focused on meso- and macroscale mathematical modeling of next-generation batteries, while leveraging advanced artificial intelligence (AI) tools to accelerate
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The Surface Scattering and Microdiffraction (SSM) group in the X-ray Science Division (XSD) at the Advanced Photon Source (APS), Argonne National Laboratory is seeking Two Postdoctoral Appointees , both focused on multimodal synchrotron characterization of defects and interfaces in oxides and 2D...
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catalyst design. This role involves conducting multiscale modeling, spectroscopy simulations, and the development of machine learning methods and automated workflows for multi-fidelity, multiscale
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Argonne National Laboratory is seeking a postdoctoral researcher with expertise in life-cycle analysis, industrial process modeling, and critical minerals and materials assessment. The appointee will
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science, and FEL user communities. The postdoctoral researcher will lead technical activities in beam-dynamics and FEL modeling, with an emphasis on start-to-end simulations of compact XFEL performance
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under the supervision of more experienced researchers. Current project opportunities include quantifying the impact of advanced vehicle technologies applicable to light duty, medium duty and heavy
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modeling, are particularly sought after. This is a one-year position that can be extended to two years that we want to fill immediately. Contributes technical expertise through analysis and support
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-based and AI/ML approaches. This position focuses on high-resolution Earth system modeling and the analysis of convective storms and weather and hydrological hazards to improve predictability
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effects of low-dose ionizing radiation. The position will contribute to the LUCID research program, a multi-institutional effort integrating experimental biology, machine learning, and mechanistic modeling
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desirable): Autonomous laboratories for chemistry, materials, biology, etc. AI/ML for predictive modeling and inverse design Generative models, reinforcement learning, and agent-based approaches to