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://arxiv.org/abs/2509.00098 ) This project sits at the intersection of artificial intelligence and materials characterization and modeling. The goal is to create an AI system that can intelligently operate
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The Chemical and Fuel Cycle Technologies division at Argonne is seeking a Postdoctoral Appointee to join a multidisciplinary team developing molten salt-based chemical and electrochemical processes
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scientists, roboticists. The project will focus on developing an integrated autonomous lab system for strucutre-property characterization of novel materials heterostructures for quantum and microelectronics
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We seek a postdoctoral scientist with expertise in electrodeposition science and technology. Exposure to microelectronics applications is desirable, as is familiarity with progamming and interfacing
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the ultrathin limit. Position Requirements We seek outstanding researchers with a strong background in experimental condensed mater physics and materials science. No prior knowledge of MBE is needed, though a
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total X-ray scattering (TXS) and pair distribution function (PDF) analysis capabilities and methodology to study laser-driven structural dynamics in functional materials. This position is part of a
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across materials science, chemistry, geoscience, energy technologies, and biology. Position Requirements This level of knowledge is typically achieved through a formal education in physics, applied physics
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The Chemical and Fuel Cycle Technologies division is seeking a Postdoctoral Appointee to join a multidisciplinary team developing processes to support molten salt reactor (MSRs) fuel cycles
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photonic platforms for hybrid quantum systems. The role offers a unique opportunity to engage in advanced materials synthesis, nanofabrication, and multimodal characterization using Argonne’s world-class
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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