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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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optimization schemes. From developing AI models to uncover structure-function relationships with limited data sets, to building automated electrode-electrolyte interface discovery workflows and implementing full
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workflows using the Model Context Protocol (MCP) to orchestrate data ingest and data movement across heterogeneous storage systems, including object stores. The postdoc will also engage with science
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of Large Language Models (LLMs) for scientific use cases. This position focuses on advancing LLM capabilities to address complex challenges across a range of scientific domains. As part of a
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operando experiments under electrical, thermal, or mechanical bias to capture real-time defect dynamics. Integrate multimodal datasets and collaborate with AI/ML teams for data fusion, physics-informed model
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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- Exploring Foundational Models and Agentic AI to address challenges in energy storage and conversion. Position Requirements Candidates must meet the following qualifications: 1. Educational Background: - A
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pressure diamond anvil cell technology. Excellent oral and written communication skills. Ability to model Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork. Preferred Knowledge, Skills
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Strong written and oral communication skills Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications Experience with block copolymer patterning
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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