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data processing and interpretation workflows. The appointee will also pursue a collaborative science program leveraging the developing instrument capabilities, leading to peer-reviewed publications and
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. The successful candidate will be a key contributor to a multidisciplinary co-design team spanning material science, computing, and electronic engineering, with the goal of enabling next-generation detector
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thin film deposition is preferred. Advanced image processing and analysis skills. Experience with micromagnetic simulation is preferred. Ability to work independently as well as in collaboration with a
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information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum
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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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-throughput workflows for data acquisition and analysis Contribute to on-the-fly data processing and integration with computational tools Collaborate with multidisciplinary teams in nanofabrication
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synchrotron-based techniques to inform process development. The role requires a strong background in synchrotron characterization techniques, mainly three-dimensional imaging (microtomography and