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experiments and corresponding data analysis. Following the successful demonstration of the technique, the candidate will collaborate with team members from material science to apply these methods to scientific
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at technical conferences. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, computer science
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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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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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techniques to solve pressing challenges in energy storage. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne
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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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, electrical engineering, materials science, or a related field at the PhD level with zero to five years of employment experience. Hands-on experience in one or more of the following: Cryogenic detectors (TES
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-completed PhD (within the last 0–5 years) with strong background in physical chemistry, photophysics, photochemistry, and polariton chemistry Hands-on experience in thin-film deposition, and spectroscopic
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progress, and funding. This is an on-site role at Argonne National Laboratory (Lemont, IL), within the X-ray Science Division (XSD) and the APS scientific user-facility. Position Requirements PhD completed
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. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple HEP experiments. Experiments with Argonne involvement include, but are not