34 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" uni jobs at National Renewable Energy Laboratory NREL in United States
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Posting Title Graduate Intern – Machine Learning - Solar Forecasting . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per Week 40 . Working at NLR NLR is located at the foothills
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reliability, resilience, and security. Our team is looking for an intern who has strong technical background in machine learning (ML) and artificial intelligence (AI), ideally on large language models, natural
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chemistry support to all research and development groups within the BEST directorate at NLR. To learn more about the research within this directorate, click here: https://www.nrel.gov/bioenergy . The team is
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issues that arise This internship will involve extensive time in a laboratory environment, and it is essential for the selected candidate to support a safe and efficient work environment To learn more
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/unix Experience with collaborative code development Experience with Machine Learning Experience with the Geospatial data abstraction library (GADL) Experience with big geospatial data processing . Job
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response, or related areas, including the use of dispatch, radio systems, and computer networks. Proficiency in Microsoft 365 tools and a willingness to learn specialized software. Ability to handle
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Learning Opportunities Gain hands-on experience with utility-grade EMT and RMS modeling tools used in industry and research Learn how data centers impact grid stability and how to model their interactions
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strategies that apply whole-of-lab research capabilities to National Security Sector partner organizations’ most critical mission requirements. To succeed, the Lead will quickly acquire detailed knowledge
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electric distribution systems research, using power-flow modeling, optimization, machine-learning, neural networks, capacity modeling, forecasting techniques, statistical analysis, and data analysis among
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, design, and analyze distribution and bulk power systems. You would join us in researching, supporting and advancing electric distribution systems research, using power-flow modeling, optimization, machine