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for developing new computational tools and AI/ML approaches to analyze and correlate data from multiple imaging modalities, including synchrotron tomography, x-ray fluorescence microscopy, visible light microscopy
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open access of datasets. Key Responsibilities Develop and implement data management strategies to support research activities across multiple institutions. Collaborate with researchers to establish data
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that can process and learn from multiple data streams in real-time is key to unlocking the full potential of such instruments. The postdoctoral appointee will be responsible for developing such methods
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multiple groups within the X-ray Science Division, the Center for Nanoscale Materials and the Materials Science Division of Argonne. Position Requirements Ph.D. in material science and engineering, physics
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analysis of (1) decarbonization pathways for energy- and emissions-intensive industries and (2) material circularity pathways in a low-carbon future. The candidate would conduct research across multiple DOE
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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