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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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Control Valves, High Pressure Gas Manifolds, Large and Small Pumps, and underground utilities. Respond to mechanical and system emergencies to identify safety hazards, prevent damage to property and assess
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machine-learning or data analysis to massive datasets, scientists today rely on advances in and integration across applied mathematics, computer science, and computational science, as well as large-scale
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Lakehouse, ensuring large scientific datasets are structured for efficient querying and analysis. * Design, build, and maintain fault-tolerant, scalable, and efficient ETL/ELT data pipelines to ingest
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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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reasoning over large scientific data sets. Developing theories for materials synthesis and degradation. Preparing presentations and reports. Writing peer-reviewed journal articles. We are looking for: PhD in
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python. Experience with machine-learning, such as training large language models. Required Application Materials: CV Cover Letter (1 page) Publication List Additional information: Application date
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Lakehouse, ensuring large scientific datasets are structured for efficient querying and analysis. * Design, build, and maintain fault-tolerant, scalable, and efficient ETL/ELT data pipelines to ingest
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scientific judgment and initiative Experience handling large datasets and ensuring data quality Proficiency with MS Office and strong skills in at least one programming language (C/C++, Python, R) Familiarity
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of Perlmutter and connect directly to DOE experimental and observational facilities so research teams can stream and analyze data in near real time. You will collaborate with NERSC staff, domain scientists, and