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at Argonne. In this role, the candidate will design, synthesize, and evaluate cutting-edge electrocatalysts for converting CO2 into valuable chemicals and enabling water splitting, and perform comprehensive
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approaches to solve challenges that go beyond the use of pilot scale or commercialized equipment. As such we are seeking candidates that have demonstrated the ability to design and build their own experimental
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optimization with computer-aided design software. Knowledge of machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and analysis of large datasets, and
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instrumentation and readout systems for innovative and leading-edge detectors and other scientific research. The successful candidate will work with design teams and scientific collaborations in the development
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years or is soon to be completed Considerable experience in at least two of the following fields: X-ray microscopy, engineering design, cryogenic microscopy, synchrotron instrumentation Strong trouble
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estimates critical to materials design. In this role you can expect to: Work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National
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The Chemical and Fuel Cycle Technologies division is seeking a Postdoctoral Appointee to join a multidisciplinary team performing process modeling, flowsheet development, and novel equipment design
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enabling their research goals on Aurora through collaboration and innovation. There are opportunities to engage with research in AI (LLMs, foundation models, etc), performance optimization, portable
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Our mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with
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National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women