39 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"St"-"St" positions at Argonne
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on developing machine-learning surrogates for electronic structure and electrostatic potential and using these models to predict structural and electronic evolution under applied bias. Methods may include density
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We are seeking a highly motivated Postdoctoral Appointee with a strong background in artificial intelligence and machine learning (AI/ML), with particular emphasis on the development and application
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, advanced computational techniques, and data science. The project involves: Materials Development Platform that will enable redox molecule optimization via predictive simulations, database management, and AI
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Roman Survey in the Cosmic Frontier, the Division is engaged in physics preparations for the EIC, the development of advanced accelerator technologies (Argonne Wakefield Accelerator), as well as in
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We are seeking a highly motivated and adaptable postdoctoral researcher to join the Laboratory Directed Research and Development (LDRD) project FREEZE (Fundamental Research on Energy-Efficient Zonal
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design, advanced modeling and high-performance computing, mathematics and data analytics, AI/ML algorithm development, and accelerator operations Ability to model Argonne’s core values of impact, safety
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conducted by developing intelligent systems that can function as collaborative partners in the scientific process. Our group is pioneering the development of (1) generative AI models and agentic architectures
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diamond membranes, defect synthesis, quantum experiment development, and optical spectroscopy. The successful candidate will join a dynamic, collaborative team working across the Argonne community and with
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; present findings internally and at external conferences; contribute to publications Collaboration Environment Work in close coordination with ML development teams across Argonne (including the Advanced
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4