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The Applied Materials Division, Process R&D and Scale up Group at Argonne National Laboratory is seeking a Postdoctoral candidate to conduct general research in material science and electrochemistry
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and lanthanides within controlled atmosphere gloveboxes. Apply chemical thermodynamic and kinetic theories to understand processes and develop models of material interactions and behavior in molten salt
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. The successful candidate will be a key contributor to a multidisciplinary co-design team spanning material science, computing, and electronic engineering, with the goal of enabling next-generation detector
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among material properties, electrochemical performance, and battery system cost at the material, cell, and pack levels. The researcher will plan and advance performance and cost modeling of energy storage
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simulations and experiments across scientific user facilities, leveraging data to understand complex material phenomena across scales. Key Responsibilities Design, implement, and validate physics-informed AI/ML
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, magneto-optic Kerr effect (MOKE) microscopy, and scanning NV microscopy. This position will also involve preparing suitable samples and devices using 2D material transfer systems and nanofabrication methods
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on securing a domestic supply chain for critical materials, such as graphite. This candidate will join a team developing and testing material beneficiation, leaching, and separation unit operations for carbon
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-informed AI framework that decodes the complex relationships between material defects, functional fields (e.g., strain, electrostatic potential), and device performance, with a primary focus on leveraging
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, or a related field at the PhD level with zero to five years of employment experience. Technical background in economics with a focus on the mineral and energy sectors. Proven scholarly work or industry
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experiments and corresponding data analysis. Following the successful demonstration of the technique, the candidate will collaborate with team members from material science to apply these methods to scientific