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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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Argonne National Laboratory seeks a postdoctoral researcher to help build a high-resolution coastal-urban flooding modeling capability within the Energy Exascale Earth System Model (E3SM
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simulations, design and conduct experiments, and analyze multimodal data streams in a continuous, real-time loop with minimal human intervention (https://www.nature.com/articles/s41524-024-01423-2 , https
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technologies, and in advancing data-driven risk monitoring approaches for supply chain resilience. The candidate will assist with data collection, analysis, and scenario modeling for a DOE-sponsored assessment
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The Energy Systems and Infrastructure Assessment (ESIA) division at Argonne provides the rationale for decision makers to improve energy efficiency. ESIA develops and uses analytic tools to help
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operando characterization using the Advanced Photon Source (APS). This work will support critical material recovery and battery recycling initiatives. The successful candidate will help drive next-generation
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target properties. The candidate will help draft and publish technical reports, conference papers, and journal publications describing the research outcome and will be expected to attend and present