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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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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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of the upgraded APS, leadership-class computing at the Argonne Leadership Computing Facility (ALCF), and state-of-the-art microscopy at the Center for Nanoscale Materials (CNM). Candidates with a strong background
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The Chemical Sciences and Engineering Division seeks a Postdoctoral Appointee to conduct research focused on the development of high-energy, long-cycle-life lithium–sulfur batteries employing both liquid and solid-state electrolytes using artificial intelligence, under the guidance of a...
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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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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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, Quantum Information and Quantum Simulation. The successful candidate will be expected to carry out an independent and collaborative research program in particle theory that strengthens and complements
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multidisciplinary team, the candidate will work at the intersection of AI/ML, domain sciences, and high-performance computing. The role requires a strong foundation in LLMs and machine learning, along with
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The Chemical and Fuel Cycle Technologies division is seeking a Postdoctoral Appointee to join an R&D team conducting use-inspired research supporting the development of molten salt technologies for application to molten salt reactors (MSRs) and molten salt fuels, pyrochemical treatment of used...
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. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence. The project involves: 1