8 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Kent" research jobs at Lawrence Berkeley National Laboratory in United States
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for materials synthesis planning and automated solar data degradation pathway analysis based on literature data. You will support two DOE projects at 50% each. The first project is the DOE BES Data-Driven
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for binding critical minerals and materials. The postdoc will be part of a collaborative team of researchers in the Molecular Foundry from the Biological Nanostructures, Data Science and Infrastructure, Imaging
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for data analysis and predictive modeling. The fellow will join a small, world-class, multi-institutional team advancing microelectronics research through AI-enhanced methodologies. You will: Perform soft X
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Letter (1 page) Publication List Additional information: Application date: Priority consideration will be given to candidates who apply by February 5, 2026. Applications will be accepted until the job
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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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-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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the scanning tunneling microscope. Prepare and characterize 2D material heterostructures in support of optical and thermal experiments. Automate parts of sample fabrication, and data analysis to improve
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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