47 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at Argonne
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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integration Optimization and stochastic modeling methodologies Energy storage Electricity market analysis Supports multidisciplinary teams in the application of these methods and tools to complex issues in
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laboratory partners, and contribute to the development of separation technologies for energy, water, and critical resources. Key Responsibilities: Develop and apply in-situ methods (e.g., optical coherence
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of advanced scanning/transmission electron microscopy (S/TEM) methods for cutting-edge scientific research in areas such as quantum materials and low-dimensional energy systems. This position emphasizes
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advanced computing, optimization, and data analytics technologies. The postdoctoral researcher will work with a team of researchers on solving challenging problems using optimization, stochastic models
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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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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