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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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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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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
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early “pathfinder” experiments that establish performance and scientific impact. This role combines end-to-end instrumentation leadership (requirements, design maturation, interfaces, test/acceptance
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Development (LDRD) project titled “Development of Tunable and Narrow Bandwidth Terahertz Light Source for Light-Active Quantum Materials.” The successful candidate will lead the design, implementation, and
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of modern AI tools to accelerate the entire research workflow—including literature exploration, experiment design, implementation, analysis, and dissemination. The researcher will work in a collaborative