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, instrumentation, modeling, and data science Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field(s) of materials science, physics, computational science, or a related field
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of reaction mechanisms in molten salts and apply insights to process development and scale up. Project activities will include the design and development of advanced sensors and flow systems for molten salts
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks a highly motivated postdoctoral researcher to join a multidisciplinary team advancing quantum information
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, interdisciplinary environment with access to large-scale computing resources and diverse scientific use cases. The position strongly supports publishing in top-tier venues, contributing to open-source research
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scientists with extensive microelectronics (materials and devices), AI, computational materials science and materials characterization expertise; and will be expected to bring the electrochemical expertise
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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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, 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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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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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence. The project involves: 1