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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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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
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, Physics, or a related field. Strong expertise in machine learning, computational imaging, computer vision, or signal processing. Proficiency in scientific programming and modern ML frameworks, with
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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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contribute to long term vision of HPCAT. Working with staff and extensive partner members (including LANL, LLNL, SNL, and numerous national and international academic and other institutions) The
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and contribute to long term vision of HPCAT. Working with staff and extensive partner members (including LANL, LLNL, SNL, and numerous national and international academic and other institutions) The
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unconventional sources. The successful candidate will work on continuous hydrometallurgical processing approaches for selective and efficient recovery of critical materials relevant to energy innovation. The
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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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technical work related to the development of new processes for metals production and processing. Prepare formal reports, make presentations, and publish to establish leadership position in R&D for