48 computer-programmer-"https:" "https:" positions at National Renewable Energy Laboratory NREL
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lead the MCCS Computational Science Center (CSC), https://www.nlr.gov/computational-science ) at the National Laboratory of the Rockies (NLR). The CSC stewards the largest HPC environment in the
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-based resources and the highly customized solutions developed by the group. The candidate should be eager to work in an interdisciplinary field, together with computer scientists, policy analysts, and
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team. The initial appointment is for one year, with possible renewal up to three years. We encourage interested candidates to see the following papers: https://pubs.rsc.org/en/content/articlehtml
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group does, check out the following link: https://www.nlr.gov/grid/distributed-energy-resource-management-systems . Basic Qualifications Minimum of a 3.0 cumulative grade point average. Undergraduate
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group does, check out the following link: https://www.nlr.gov/grid/distributed-energy-resource-management-systems . Basic Qualifications Minimum of a 3.0 cumulative grade point average. Undergraduate
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. In conjunction with the DOE’s METALLIC platform ( https://netl.doe.gov/metallic ), we are developing a closed-loop autonomous experimentation platform that integrates scientific instrumentation, data
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to guide experiments. For some sample publications by the group please visit the below links albeit please note this is more of an experimentalist position compared to characterization. https
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address U.S. economic, security, and environmental priorities. Description of capabilities and recent air quality focused projects can be found here: https://www.nlr.gov/analysis/air-quality.html . The
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to conduct research at the intersection of machine learning, computer vision, large-scale data analytics, and photovoltaic (PV) system performance . The successful candidate will join a
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laboratory environment, the intern will develop and validate computer vision pipelines — including semantic segmentation models — for automated site identification, sample quality assessment, and adaptive ion