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and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning multiple DOE user
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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
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conferences, and work within a large, interdisciplinary team of experts from multiple national laboratories and universities. The appointee will benefit from direct access to the unique capabilities
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characterization, computational modeling, and artificial intelligence across multiple academic and national laboratories. Key Responsibilities Design and execute S/TEM imaging and spectroscopy, including in situ
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engage across multiple projects and research applications. Experience in the following areas is a preferred and will help the candidate succeed: Li-ion batteries, materials characterization, critical
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Qualifications: Ph.D. (completed within the past 0-5 years) in computer science, electrical engineering, applied mathematics, or a related field. Strong proficiency in Python, with additional experience in C, C
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open access of datasets. Key Responsibilities Develop and implement data management strategies to support research activities across multiple institutions. Collaborate with researchers to establish data
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multiple groups within the X-ray Science Division, the Center for Nanoscale Materials and the Materials Science Division of Argonne. Position Requirements Ph.D. in material science and engineering, physics