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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, and
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on advanced battery materials using electrochemical, structural, and chemical characterization methods Fabricate and evaluate prototype battery electrodes and pouch cells in a dry-room environment Collaborate
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, dendrite growth, side reactions, delamination, and related behavior in hard and soft materials. A strong emphasis will be placed on the integration of AI methods and agentic workflows into model development
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, who develop hardware and software infrastructure for laboratory autonomy, support autonomous laboratories in domains including chemistry, biology, and quantum science, work with domain scientists
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cathode materials for lithium-ion and sodium-ion batteries. This work will include the use of advanced synthesis methods, electrochemical testing, and state-of-the-art characterization techniques
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techniques to industrial energy systems, manufacturing systems, and commodity supply chains. Integrate data-driven methods with optimization-based modeling frameworks, including linear, mixed-integer
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The Applied Materials Division at Argonne National Laboratory has an immediate opening for a Postdoctoral Appointee. The candidate will be responsible for reviewing and developing design methods and
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. Position Requirements A formal education in Physics, Materials Science, Chemistry, or a related field at the PhD level with zero to five years of employment experience. Demonstrated experience with high
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), in collaboration with Argonne researchers and external partners from industry and academia. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in
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, software systems, simulation capabilities, and experimental workflows for connecting quantum devices with classical computing and networking infrastructure. The successful candidate will work in a