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models for high-temperature structural materials with applications in nuclear reactors and other energy systems. The candidate will collaborate with ANL staff to review, validate, and enhance methods
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agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware spectroscopy workflows. The researcher will work closely with a multidisciplinary team of X-ray physicists and
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/modelers, and data scientists Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of Materials Science, Chemical Engineering, Chemistry, or a closely related field
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foundational models to describe IDP interactions under various physiological conditions, both normal and cancer related Use these models to iteratively design, validate, and refine experiments, leading
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independently and conducting beam experiments. Strong knowledge of accelerator theory, accelerator modeling and simulation, beam control, and beam diagnostics. Familiarity with EPICS-based control systems in a
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design, fabrication, and/or measurement Proficiency in low-noise cryogenic measurement techniques at millikelvin to few-kelvin temperatures Ability to model Argonne's core values of impact, safety, respect
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We are seeking a highly motivated postdoctoral researcher to conduct independent research on foundation models for scientific and engineering applications, with an emphasis on training, adaptation
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to accelerator operations. Experience working with complex algorithms and data-driven models. Experience using high-performance computing clusters for simulation and data analysis. Ability to model Argonne’s core
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the development of AI models for robotic control and the demonstration of these methods via simulation and experiment. Beyond the listed projects, the candidate may contribute to other large-team scientific
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workflows using the Model Context Protocol (MCP) to orchestrate data ingest and data movement across heterogeneous storage systems, including object stores. The postdoc will also engage with science