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-the-loop exploration of extreme-scale scientific data. This position sits at the intersection of scientific visualization, agentic AI systems, human–computer interaction (HCI), and high-performance computing
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for dynamics imaging. The primary goal of this project is to develop single-frame ptychography methods that eliminate the need for scanning, enabling fast imaging and the visualization of dynamic processes in
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, distributions, and dynamics in metallic, oxide, and semiconducting systems. This project integrates high-throughput and in situ TEM experimentation with AI/ML-driven image analysis and computational modeling
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lead efforts to develop experimental techniques using conventional and coherent imaging in the ultrafast time domain, as well as a computational framework for modeling and reconstructing images
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Argonne National Laboratory invites applications for postdoctoral research positions in experimental physics, with a focus on advancing superconducting particle detector technology for next
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chemistry, chemical engineering, physics, computational science, materials science, or related field. Background in synchrotron characterization techniques. Experience collecting and analyzing large