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. As part of a multidisciplinary team spanning multiple Argonne divisions, you will contribute to the design, fabrication, and characterization of superconducting devices based on high kinetic inductance
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address next-generation HEP and NP detector challenges. The postdoctoral appointee will collaborate closely with leading scientists across multiple divisions at Argonne. Key Responsibilities Elicit and
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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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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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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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workflows. 3. Programming Skills: - Proficiency in C++/or Python programming languages is essential. 4. Research Contributions: - Demonstrated publications in AI for Materials Chemistry. 5. Collaboration and
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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