25 data "https:" "https:" "https:" "https:" "I.E" "UCL" "UCL" positions at Lawrence Berkeley National Laboratory
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National Laboratory is hiring a Data Science Workflows Architect within the NERSC division. The National Energy Research Scientific Computing Center (NERSC) is seeking an engineer with experience in complex
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new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities. This role involves research and
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computer science, mathematics, data science, or any computational science discipline who have received their Ph.D. and have completed no more than three years of postdoctoral work are encouraged to apply. Only one
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-the-house core-level spectroscopy, i.e. X-ray Photoelectron Spectroscopy, X-ray Adsorption Spectroscopy, etc., as well as chemistry domain knowledge, to come up with a unified mechanistic explanation that is
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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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. 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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exploration of nonlinear optical and superconducting materials heterostructures. The postdoc will be part of a collaborative team of researchers in the Molecular Foundry from the Inorganic Nanostructures, Data
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accurate written reports to applicable standards and ensure that this information is entered into the industrial hygiene database as applicable. Attend regularly scheduled Team, Department and Division
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. Additional Responsibilities as needed: Safe handling of solvents, nanofillers, high-voltage testing, and instrument SOPs; participation in EHS trainings and near-miss reporting culture. Reproducibility & data
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expertise, facilitate the cross pollination of skills, provide training, centralize toolsets and data management, as well as agilely shift resources to support projects and divisions across the Laboratory