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into a scientific context through multi-modal modeling/LLM RAG/etc. Build strong collaborations within ORNL and across the global research community. Publish groundbreaking research in top-tier machine
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liquids, frustrated magnetism, excitonic magnets, and strongly correlated electron systems. You will work closely with theorists, experimentalists, and computer scientists to build robust, scalable
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of geothermal wells, reduce costs, improve productivity, and mitigate risks. The project builds upon previous MEERA work focusing on casing and cementing activities that identified the cost of casing, cement and
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an emphasis on circular economy research Demonstrate an understanding of renewable and onsite energy technologies including experience with industry and/or buildings, specifically with the implementation
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Manufacturing Demonstration Facility (MDF). This role offers a unique opportunity to drive impactful research on sparse scientific imaging while building a strong research profile in computational imaging and ML
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, MLSys/SC/HPDC). Hands-on with distributed training/inference (FSDP, DeepSpeed, Megatron-LM), accelerator programming, and large-scale data pipelines. Experience building agents that use tools/APIs (e.g