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, electrical characterization, and electrochemical measurements. Perform interfacial characterization to understand bonding mechanisms between nanomaterials and matrix phases. Analyze experimental data, develop
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ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real
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technology research and development by fabricating prototype electrodes and pouch cells in a dry-room environment and by contributing to experimental design, data interpretation, and technical reporting
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processes Implement models and perform numerical simulations Analyze and interpret simulation and experimental data Integrate AI tools and workflows to enhance modeling and accelerate learning Collaborate
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analyze data, and effectively report results. The position requires hands-on laboratory work to develop and synthesize new organic materials and to develop, carry out and analyze results of analytical and
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, battery electric and fuel cell powertrain design, development of supervisory control logic, validation of vehicle models against test data etc. The projects and interests of this group span all modes
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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in chemical engineering, materials science, chemistry, or a closely related field Expertise in crystallization science, including
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-completed PhD (typically completed within the last 0-5 years)in Chemistry, Chemical Engineering or Materials Science (those with other degrees but have similar skills to those listed will be considered
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work within a multidisciplinary team with researchers at MERF and collaborators inside and outside Argonne. The candidate is expected to design and conduct experiments, analyze data and explore
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of cathode operation and degradation, and identify pathways to improve the performance and safety of advanced electrochemical cells Analyze and interpret experimental data and communicate findings through