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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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and integrate emerging AI techniques (e.g., agentic workflows, LLMs) into scientific problems, ensuring methods effectively solve real domain challenges. Advanced Model Development: Design and debug
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, advanced characterization, nanofabrication, and theory/modeling. Key Responsibilities: Perform transmission electron microscopy and spectroscopy, including in situ and ultrafast measurements Design and
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simulations and experiments across scientific user facilities, leveraging data to understand complex material phenomena across scales. Key Responsibilities Design, implement, and validate physics-informed AI/ML
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Mathematics, or a closely related field. Design and optimize multimodal LLMs to encode, fuse, and reason over heterogeneous scientific data from diverse modalities such as numerical tables, text, and images
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design, develop, and evaluate AI-driven scientific visualization assistants that support intuitive, context-aware interaction with large-scale simulation and experimental data. The postdoc will focus
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
, physics-informed AI agent that accelerates discovery in catalysis science—particularly for the CO₂ reduction reaction (CO₂RR) and oxygen evolution reaction (OER). The postdoc will design and perform
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
vulnerabilities. The Postdoctoral Appointee will be responsible for the conceptual framework, design, and implementation of these models, ensuring scalability on the DOE’s leadership computing facilities. Position
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fabrication, including mask design, metal sputtering, laser or e-beam lithography, etching, and device integration Familiarity with thin-film materials (e.g., oxides, dielectrics, metals) and their integration
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and written communication skills in scientific and engineering contexts. Ability to integrate diverse knowledge and perspectives to drive innovation. Experience working independently and collaboratively