Graduate Intern – Machine Learning - Solar Forecasting

National Renewable Energy Laboratory (NREL) is the nation's primary laboratory for energy systems research and development. They are seeking a full-time graduate engineering intern to develop and implement AI algorithms for real-time solar forecasting, leveraging expertise in machine learning and statistics.

Responsibilities

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

Skills

• Minimum of a 3.0 cumulative grade point average
• Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution
• Post Undergraduate: Earned a bachelor's degree within the past 12 months. Eligible for an internship period of up to one year
• Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution
• Post Graduate: Earned a master's degree within the past 12 months. Eligible for an internship period of up to one year
• Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution
• Completed a Bachelor's degree and either have completed a master's degree or be enrolled in a masters or PhD degree in 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
• Hands-on experience in energy related time series forecasting, such as participating in energy forecasting competitions
• Experience in multi-modal machine learning
• Knowledge about PV plants, PV inverters, and PV control
• A track record of producing high quality research papers

Benefits

• Medical, dental, and vision insurance
• 403(b) Employee Savings Plan with employer match*
• Sick leave (where required by law)
• Performance-, merit-, and achievement- based awards that include a monetary component
• Relocation expense reimbursement

Company Overview