36 machine-learning positions at National Renewable Energy Laboratory NREL in United States
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Posting Title Graduate PhD Student (Year-Round) Machine Learning Applications for Cyber-Physical Power System Operations Intern . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per
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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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. This project explores a new paradigm: Learning to Optimize for large-scale Mixed-Integer Nonlinear Programming (MINLP) problems in Unit Commitment. By combining machine learning with structured optimization
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understanding of power semiconductor module selection and characterization. Preferred Qualifications Background in databases, electrical-engineering-oriented machine learning, and fault diagnostics of electric
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modeling, exploratory data analysis, machine learning workflows, and reproducible research methods that enable scientific insight and decision‑support for energy systems analysis.. The Data Engineering team
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sensor placement and communication design Develop and train machine learning model to estimate and forecast grid edge conditions Support grid applications such as DER aggregation and voltage control
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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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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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-native, microservice-based systems that apply machine learning and advanced analytics to real network data, contributing to next-generation autonomous networks. Key Responsibilities Design and implement
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comprehensive hazard-based training programs for Laboratory personnel, translating regulatory directives into impactful learning experiences that support operational resilience and safety culture. Coordinate and