Graduate Intern – Machine Learning, Solar Forecasting

November 23

⛰️ Colorado – Remote

Although this job is listed in Colorado, this company may be open to hiring remote in other states.

💵 $50.2k - $80.3k / year

👨‍🎓 Internship

⚪️ Entry-level

🤖 Machine Learning Engineer

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National Renewable Energy Laboratory

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Energy • Science • Government

National Renewable Energy Laboratory is a national laboratory of the U. S. Department of Energy, focused on transforming energy through research, development, commercialization, and deployment of renewable energy and energy efficiency technologies. NREL partners with organizations to accelerate the transition of these technologies to the marketplace. The laboratory covers a range of research areas, including bioenergy, geothermal, hydrogen, solar, transportation, wind, and water. It provides data sets, maps, models, and tools for energy analysis and offers research positions in various fields related to renewable energy. NREL is committed to economic impact, sustainability, diversity, and community collaboration.

1001 - 5000 employees

Founded 1977

⚡ Energy

🔬 Science

🏛️ Government

📋 Description

• Innovate and Optimize: Build best-in-class models for inverter-level and plant-level solar forecasting with calibrated uncertainty, using RNN, diffusion models, and graph models • Implement and Impact: Bring your algorithms to life for industry partners, making tangible improvements in solar forecasting • Lead and Collaborate: Manage our project GitHub repository for experiment tracking and code versioning, ensuring seamless collaboration with partners and code excellence • Share Your Discoveries: Present your groundbreaking results and key findings at workshops, conferences, and in high-quality journals, positioning yourself as a thought leader in the field

🎯 Requirements

• Minimum of a 3.0 cumulative grade point average • Must be enrolled as a full-time student in a master’s degree program from an accredited institution • Must have completed a bachelor’s degree within the past 12 months • Completed a Bachelor's degree and either have completed a master's degree or be enrolled in a masters or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Applied Math, or a related analytical domain • Demonstrated knowledge and experience in Python and its related libraries, such as TensorFlow, Keras, and Pytorch • Demonstrated experience in time series forecasting, computer vision, and scenario generation • A comprehensive understanding of uncertainty quantification. • Demonstrated experience documenting and presenting results in presentations, papers, and or publications.

🏖️ Benefits

• medical, dental, and vision insurance • 403(b) Employee Savings Plan with employer match* • sick leave (where required by law)