7 data-"https:"-"https:"-"https:" Fellowship positions at Lawrence Berkeley National Laboratory in United States
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-tuning and/or Retrieval-Augmented Generation (RAG) methods to augment LLMs with dedicated knowledge in transportation and electric grid domains. This involves designing methods to process input data and
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design and implement mitigation strategies. Validate, analyze, and interpret experimental data. Firmware development & programming tools to interface with FPGA-based electronics. Quantum verification and
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accessible gate-based quantum computer. Our technology platform is based on superconducting quantum circuit processors, and we aim to generate the detailed experimental findings needed to resolve foundational
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data. Communicate results through peer-reviewed publications, technical reports, conference presentations, and sponsor engagement. Build collaborative networks across Berkeley Lab and the DOE national
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the development and application of a digital twin approach, aimed at bridging the gap between theoretical predictions, data interpretation, and experimental/spectroscopic observations. What You Will Do: Design
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of Perlmutter and connect directly to DOE experimental and observational facilities so research teams can stream and analyze data in near real time. You will collaborate with NERSC staff, domain scientists, and
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for near-real-time data analysis. Your work will help 12,000+ users run faster, more reliable science. What You Will Do: Contribute to one or more NESAP scientific workflows targeting NERSC HPC resources