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Argonne National Laboratory is seeking a scientist to help advance the emerging field of networked and distributed quantum computing. This position offers the opportunity to shape new architectures
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and electrocatalysis, including: catalyst design mechanistic studies microkinetic modeling reactor modeling Strong computational expertise in applying quantum mechanical methods to determine electronic
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applying artificial intelligence (AI) and machine learning (ML) methods for the autonomous, self-driving synthesis of nanoscale and quantum materials. This is an exciting opportunity to help shape a new
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In the Computational Materials Group, we focus on the development and use of computational and theoretical methods to understand and predict the behavior of solids, liquids, and nanostructures from
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, vapor transport, flux growth, Bridgman growth, and related methods. Additional desirable qualifications include expertise in crystal structure determination using X-ray diffraction; experience with bulk
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research. The position plays a central role in strengthening the CNM user science program, with a particular focus on electron microscopy and synchrotron-based X-ray microscopy at the Advanced Photon Source
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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 Computing, Environment, and Life Sciences (CELS) Directorate seeks an outstanding scientist to lead and support frontier research at the intersection of AI, autonomous platforms, data
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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