22 data-"https:" "https:" "https:" "https:" "https:" "https:" "SciLifeLab" positions at Lawrence Berkeley National Laboratory
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methodology Assist with code optimization and integration into Department of Energy (DOE's) applications running on the exascale computer systems with GPU accelerators We are looking for: PhD or equivalent
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limited data. The successful candidate should have a technical/quantitative background (engineering or economics) and strong experience conducting engineering assessments and/or economic analysis. Some
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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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while ensuring reliable operations, safety, and data quality. During the ALS upgrade , you will serve as the scientific lead for 12.2.2 adjustments and upgrades, using the pause in routine operations
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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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electronics and HPC is to make more efficient use of transistors through architecture specialization, application-specific acceleration, and compilers/programming-models that better control data movement than
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. templates, etc) to ensure the highest level of quality, consistency and accessibility of ELR's service portfolio. Develop data-driven Employee Relations strategies by using metrics and trend analysis
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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