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to detector/system modeling and optimization for count rate, resolution, and throughput. Document methods and develop user-facing procedures and best practices for reliable operation during user runs
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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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four staff members [Ian Cloët, Alessandro Lovato, Anna McCoy, and Yong Zhao] and several postdocs and students. The group has a broad research program in QCD/hadron physics and nuclear structure
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) methods. The materials and devices would consist of patterned multilayer magnetic thin films, ferroelectric materials such as Zr-doped HfO2, as well as novel quantum materials. Of particular interest is the
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in detection and analysis of rare noble gas isotopes through Atom Trap Trace Analysis (ATTA), an efficient and selective atom counting method based on laser cooling and trapping. This position will
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computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the
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chemical analysis methods (e.g., SEM, TEM, XRD, XPS, FTIR) Strong background in laboratory practices and data analysis Excellent written and verbal communication skills Demonstrated ability to work
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math, HPC, signal processing, computational physics and materials science. The appointee will benefit from access to world-leading experimental and computational resources at Argonne including some of
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-augmented AI tools Interfacing AI tools with experimental facilities at CNM and Argonne Key Responsibilities Research leadership (50%) Develop and lead an independent and collaborative research program in
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, electrochemical floating tests, impedance spectroscopy, and battery performance testing Familiarity with in-situ characterization methods (e.g., FT-IR, XAS, TEM) to investigate interfacial reactivity and analyze