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