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, Aurora) and one of the brightest synchrotron x-ray sources in the world (APS). Candidates with a background in deep learning, computational physics, computational materials science, inverse problems
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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We invite you to apply for a Postdoctoral Appointee position in the Chemical Sciences and Engineering Division (CSE) at Argonne National Laboratory. This position focuses on advancing research in
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teamwork Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is $70,758.00-$117,925.00. Please note
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processing with electrochemical performance objectives, establishing scalable synthesis workflows, and supporting technology transfer. The position involves close collaboration with multidisciplinary teams
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of photosensitizers and solar fuels catalysts to be interrogated in-situ, under operando conditions and with atomic-scale resolution. Position Requirements The successful candidate will be highly motivated and have a
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of employment experience. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is $70,758.00-$117,925.00
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electrochemical characterization of designer interfaces. Position Requirements The successful candidate will be highly motivated and have a strong track record in problem solving and scientific publications
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, Safety, Respect, Integrity, and Teamwork. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is
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publications, and other regular channels. Develop technical ideas and proposals to advance the application of molten salts to chemical and electrochemical processes. Position Requirements This level of knowledge