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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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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior
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The X-ray Imaging Group (IMG) of the Advanced Photon Source (APS) is seeking a postdoctoral researcher with expertise in computational science and image processing to develop innovative methods
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Intelligence, Machine Learning, Quantum Information and Quantum Simulation. The successful candidate will be expected to lead an independent research program in particle theory to strengthen and complement
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., Argonne’s TDCosim) for integrated analysis of microgrids, DERs, and utility-scale systems; implement methods to synchronize transmission-focused simulators with distribution-level tools. Demonstrate
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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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) 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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-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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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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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R