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processing approaches and dry head-end separations methods; evaluating process performance; and contributing to technical reports, publications, and sponsor deliverables. The successful candidate will work
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developing advanced AI/ML models for applications in physics, chemistry, or materials science Experience with periodic simulation codes such as VASP Proficiency in Python programming Excellent written and oral
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory is seeking postdoctoral researchers to work on quantum devices and experiments. The project aims to develop superconducting
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Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of chemistry, geochemistry, chemical engineering, physics, materials science, or a closely related field Strong experience with
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, physics, computer science, and/or data science Demonstrated accomplishments in materials informatics, scientific machine learning, or AI-guided experimental design Strong Python and scientific computing
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(CSTR), with control over morphology, particle size, and composition Conduct physical, chemical, thermal, and electrochemical characterization of layered oxide cathode materials using a range of
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Develop and apply operando diagnostic tools for aqueous battery research Design, perform, and analyze electrochemical and materials characterization experiments Use imaging and sensing techniques, including
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solid electrolytes. We are seeking candidates who will be able to design experiments and develop methodologies to design material compositions, ink rheological properties, and coating and drying process
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from various scientific backgrounds (Physics, Chemistry, Materials Science, Geoscience, and Engineering, etc.) will be considered. Recent or soon-to-be completed PhD (within the last 0-5 years) in
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scientific discovery. Research areas include solid-state batteries with lithium and sodium metal anodes, as well as the morphology evolution of materials coupled with electrochemical and mechanical phenomena