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-impact national security missions. We are seeking a technical contributor in AI/ML research to build models and pipelines, design and implement evaluations and benchmarks, and disseminate results through
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modeling, surrogate models, and agent policies to guide experimental decision-making for materials discovery. Develop robust automation pipelines that orchestrate data acquisition, analysis, experimental
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a particular emphasis on error-corrected methods for future fault-tolerant quantum computing. The algorithms will be designed to address key models of quantum materials, such as the Hubbard model
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Requisition Id 15709 Overview: We are seeking a Postdoc who will focus on urban-scale energy modeling. This position resides in the Grid Interactive Control Group in the Energy Systems
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national security, proliferation detection, and nuclear forensics applications. This position resides in the Collection Science and Engineering Group in the Material Characterization and Modeling Section
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strategic analysis and modeling research activities of advanced materials, supply chain, and advanced manufacturing technologies for various DOE program offices. The latest analyses focus on DOE’s Advanced
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
. Focus will largely be in developing and deploying such AI/ML algorithms, closely collaborating with theorists and experimentalists to realize physics- models and/or physics-aware ML-models that can bridge
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Requisition Id 15663 Overview: We are seeking a Post Doctoral Research Associate who will focus on high fidelity building energy modeling and advanced control. This position resides in
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Requisition Id 15623 Overview: We are seeking a Research Scientist who will support a growing portfolio of research in large vision-language models, privacy preserving federated learning techniques
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focus on designing architectures and models that effectively capture the complexities of data, provide robust confidence estimates in predictions, and generate compressed quantities of interest tailored