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direction to members of the catalysis staff by defining group research goals, strategies for achieving these goals, and then implementing these strategies in order to maintain a high-profile research program
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the Argonne energy storage ecosystem, working closely with the Argonne Collaborative Center for Energy Storage Science (ACCESS). Continue a world-class research program related to energy storage and
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optoelectronics. The successful candidate will build and lead an innovative research program in microelectronics by leveraging CNM’s unique strengths in materials synthesis, device fabrication, and characterization
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contributing to multidisciplinary projects and externally sponsored programs. The scientist will produce high-impact research, broadly useful software and systems capabilities, and sustained collaborations
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facilities, including synchrotron and neutron-scattering centers. The position offers the opportunity to establish and lead an independent research program while working closely with scientists across the QSCM
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. In this role, you will lead a research program centered on AI-driven autonomous synthesis, including: Active learning and Bayesian optimization over synthesis parameters such as precursors, temperature
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infrastructure, and domain science. The candidate will have established expertise across automated and autonomous experimental platforms and AI in addition to leadership of multi-disciplinary research programs and
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symmetries, and nuclear data. LER also plays a critical role for the ATLAS National User Facility, where it provides support for ATLAS Users, conducts its own research program, and develops and operates
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The Group Leader (GL) for the Electron and X-ray Microscopy (EXM) Group at the Center for Nanoscale Materials (CNM) develops, leads, and executes world-class R&D programs in electron and X-ray
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an independently-funded research program within 2-3 years. The successful candidate will develop and apply advanced data-driven methodologies to accelerate discovery in materials/chemistry design, characterization