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to fundamental hydrological, mechanical and biogeochemical processes in soils, sediments and rocks. Setup and conduct laboratory analysis of geomaterial samples. Conduct data processes, analytics and communicate
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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
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scientists to integrate state-of-the-art AI with simulation and data analysis, including modern agentic approaches. Publish and present results in peer-reviewed venues. Examples of NESAP project themes
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phases of the scientific lifecycle, supporting the efficiency and effectiveness of capabilities for data analysis, data management, data storage, computation, machine learning, and related IT needs
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control--and contribute to data management, radiological characterization, sample collection and analysis, and air monitoring. The position also involves implementing radiological work controls, supporting
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on new assignments and may coordinate activities of other personnel. Network with key contacts outside your own area of expertise. Work on and resolve complex issues where analysis of situations or data
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science, physics, mechanical engineering, applied math, theoretical neuroscience, or statistics. In depth experience with control theory and machine learning for analysis of neural population data. Experience with
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-of-the-art quantum processors and paving the way for scalable quantum computers. This project will involve theoretical and numerical analysis of Rydberg mediated interactions of a single atom with a micro
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) research. About Computing Sciences at Berkeley Lab: Whether running extreme-scale simulations on a supercomputer or applying machine-learning or data analysis to massive datasets, scientists today rely
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computer science and high-performance computing (HPC) research. About Computing Sciences at Berkeley Lab: Whether running extreme-scale simulations on a supercomputer or applying machine-learning or data analysis