25 machine-learning-"https:"-"https:"-"https:"-"UCL"-"UCL" positions at Lawrence Berkeley National Laboratory
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Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher -- Scientific Machine Learning (NESAP) to join the Workflow Readiness team as part of NERSC's
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need experience in a receiving environment, knowledge of DOT regulations, strong communication skills, and must possess computer skills necessary to create, sort, and manage e-mail and to utilize
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in materials or low temperature physics. Demonstrated knowledge of Python or another major programming language for data analysis and familiarity with machine learning approaches for data analysis
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. Collaborate with physicists, computer scientists, mathematicians and engineers across LBNL divisions to define software requirements, implement robust solutions, and develop software for high-energy particle
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Modeling. Machine Learning Interatomic Potential (MLIP) accelerated simulations. Demonstrated ability of coding in Fortran, Shell, or Python with development experiences. Deep knowledge in excited states and
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recognized four year apprenticeship program in plant maintenance or completion of an accredited two-year program with two years of work experience; or an equivalent combination of documentable military or
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. Excellent computer literacy, including proficiency in internet browsers, email, Microsoft Office & Google Suite, advanced information management systems, and data visualization tools. Advanced skills in
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Geosciences division is hiring an Autonomous Material Processing Postdoctoral Fellow to help transform how critical materials are produced. In this role, you'll bring together machine learning, real-time
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data analysis, simulation, and machine learning, integrating resources across multiple facilities. NERSC's next major supercomputer, Doudna, will combine next generation GPUs, networking and storage
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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