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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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preservation (e.g., glycerol stocks, subculturing), aseptic technique, and operation under BSL-1 and BSL-2 containment requirements. Experience with microbial molecular biology techniques, including DNA/RNA
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Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow
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experiments. Experience: Ph.D degree in the field of Condensed Matter Physics, experimental High Energy Physics, Quantum Information Science, or a closely related discipline. Demonstrated experience in quantum
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is supported by a DOE-funded research program on ultrafast science involving Argonne National Laboratory, University of Washington, and MIT. The goal of this research program is to understand and
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, we encourage applicants to consider how their data processing and software development capability fits into the proposed work and future direction. The Postdocs will be working directly with assigned
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-ion battery recycling processes. This will require innovative approaches to solve challenges that go beyond the use of pilot scale or commercialized equipment. As such we are seeking candidates
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The position is part of a new collaboration between Argonne National Laboratory, the University of Notre Dame, and UIUC, supported by the Quantum Information Science Enabled Discovery 2.0 (QuantISED
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The Applied Materials Division (AMD) at Argonne National Laboratory is seeking a Postdoctoral candidate in the area of organic chemistry with focus on battery electrolyte materials. This position
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High Energy Physics Division, the successful candidate will contribute to the design, fabrication, and characterization of superconducting devices based on microstrip-coupled TES technology, with