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capable computers. The division aims to build lab-wide cross-cutting simulation application capabilities integrating with mathematics, computer science, domain science, and advanced computing architectures
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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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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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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory invites applications for a postdoctoral research position focused on developing AI/ML methods for autonomous materials
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. This is an exciting opportunity to work within a collaborative group with deep expertise in silicon detectors, Trigger/DAQ (TDAQ) systems, software, and computing. The Argonne ATLAS group plays a
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branches of physical sciences, or in math, computer science, and electric engineering who have an interest in accelerator physics will also be considered. Strong programming skills. Proficiency in the
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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
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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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with computational scientists in other divisions, including Mathematics and Computer Science (MCS) and the Argonne Leadership Computing Facility (ALCF). The group has significant involvement in three
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backscatter diffraction, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral