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projects in artificial intelligence, materials engineering, chemistry, and beyond at Argonne National Laboratory. Position Requirements Recently completed PhD within the last 0-5 years in computer
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data
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, experience in scaleup is a plus. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry and/or closely related discipline. Expertise in the study
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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for predicting the reliability of high-temperature structural components. This involves working with various continuum damage mechanics models and statistical reliability models. The goal is to enhance engineering
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The Data Science Learning Division at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting-edge computational and systems biology research. The primary focus
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data to guide intelligent data processing strategies and inform detector and readout device design Work collaboratively within a cross-disciplinary team and contribute to publications and presentations
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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The Advanced Photon Source (APS) POLAR beamline is seeking a Postdoctoral Appointee to develop and employ advanced high-pressure instrumentation for x-ray spectroscopy and scattering techniques