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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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by multiple orders-of-magnitude. This is an exciting opportunity to be at the forefront of using advanced computational methods and systems, including machine learning, to develop data and computing
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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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., 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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, 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
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The Advanced Photon Source (APS) at Argonne National Laboratory invites applications for a postdoctoral position focused on developing novel computational approaches for multi-modal biomedical image
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for quantum information science, but many open questions remain regarding how to control the morphology and crystallinity of these host materials for exemplary performace as hosts for optically addressable spin
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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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: Experience in atomic layer deposition (ALD) and electrochemistry. Familiarity with spectroscopic ellipsometry, atomic force microscopy, and thin film characterization methods. Job Family Postdoctoral Job
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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