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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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. The successful candidate should have expertise and experience in process modeling, techno-economic analysis (TEA) and life cycle analysis (LCA) of lithium-ion batteries and/or recycling and resources to products
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- Exploring Foundational Models and Agentic AI to address challenges in energy storage and conversion. Position Requirements Candidates must meet the following qualifications: 1. Educational Background: - A
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conducted by developing intelligent systems that can function as collaborative partners in the scientific process. Our group is pioneering the development of (1) generative AI models and agentic architectures
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The Theory and Modeling Group at the Center for Nanoscale Materials (CNM), Argonne National Laboratory (near Chicago, Illinois), invites applications for a postdoctoral appointment focused on theory
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beyond the Standard Model, including effective field theories and perturbative QCD, phenomenology at current and future colliders, as well as emerging areas in Artificial Intelligence, Machine Learning
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qualified candidates to conduct theoretical research on dark matter and physics beyond the Standard Model, with a particular emphasis on opportunities enabled by novel quantum magnonics technologies
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/ML model development to design and discover redox-active materials with tunable properties (structure, charge state, etc.) Discovery of novel materials for energy storage and conversion and their
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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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computational science expertise. The Computational Science (CPS) Division focuses on solving the most challenging scientific problems through advanced modeling and simulation on the most capable computers