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The Argonne Leadership Computing Facility’s (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing
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environment that brings together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for
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computing, including distributed computing, high-performance computing (HPC), or machine learning (ML) Interest in Standard Model measurements and/or searches for new phenomena Application Review Review of
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these fforts. A successful candidate will collaborate with scientists in DIS, Environmental Sciences division and Argonne leadership Computing Facility to further develop the AI foundation models
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close
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complex algorithms. Experience using computing clusters for simulation and data analysis. Experience with accelerator modeling and simulation codes, such as Elegant and Cheetah. Experience with SDDS, Tcl/Tk
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Directed Research and Development (LDRD) project. This research focuses on understanding how critical elements are distributed at mineral-water interfaces, with the goal of revealing the fundamental
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PhD and undergraduate students, prepare technical reports and manuscripts, and support future project applications. Major Duties / Responsibilities: Advance synthetic techniques to develop existing
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, conferences, symposia, and seminars. Position Requirements A formal education in materials science and engineering, nuclear engineering, or a related field at the PhD level with zero to five years of
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closing this gap. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary