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National Lab's (LBNL ) NERSC Division has an opening for a Machine Learning Engineer to join the team. In this exciting role, you will serve as a Machine Learning Engineer in NERSC's Data and AI Services
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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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requires a high-degree of team work and interdisciplinary activities. What You Will Do: Perform research in machine learning methods based on control theory applied to problems in neuroscience. Prepare write
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-binding approaches. Proficiency with major simulation packages such as ASE, Quantum ESPRESSO, VASP, CP2K, or LAMMPS, and their Python interfaces. Working knowledge of machine learning techniques in
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Instrumentation Development System (BIDS). Comfortable in a Linux environment. Knowledge of Rust. Knowledge of quantum information science and experimental and analytical experience. Knowledge of machine learning
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performance. Relevant publication record and clear, effective written/oral communication of scientific results. Knowledge of quantum information science relevant to the responsibilities above. Proven ability to
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and Berkeley Lab. Alvarez Fellows apply advances in computer science, mathematics, computational science, data science, machine learning or AI to computational modeling, simulations, and advanced data
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science discipline of interest to the Computing Sciences Area and Berkeley Lab. Alvarez Fellows apply advances in computer science, mathematics, computational science, data science, machine learning or AI
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technologies: C, shell, and Python programming languages Git, runners, and complex CI/CD pipelines Using and developing AI (or machine learning) tools and services Database administration and optimization
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results to the research group. Develop and apply numerical methods, including machine learning tools, to improve understanding of hydro biogeochemical processes, such as evapotranspiration and carbon