National Laboratory of the Rockies · 18 hours ago
Graduate (Summer) Intern - Distributed Energy Systems
The National Laboratory of the Rockies (NLR) is focused on energy innovation through research and systems integration. They are seeking a Graduate Intern to assist in developing optimization and control models for power systems and distributed energy resources, with responsibilities including analyzing utility data and developing machine learning models.
Clean EnergyCleanTechEnergyRenewable Energy
Responsibilities
Analyze utility feeder data
Analyze grid topologies and data corrections
Quantify grid visibility criteria and conditions
Determine best locations for 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
Qualification
Required
Must be enrolled as a full-time student in a Bachelor's, Master's or PhD degree program, or graduated in the past 12 months from an accredited institution
Candidates who have earned a degree may work for a period not to exceed 12 months
Must have a minimum of a 3.0 cumulative grade point average
Demonstrated knowledge and experience with machine learning and deep learning, power system data analytics
Preferred
Distribution system modeling
Distribution system monitoring and forecasting
Detection and estimation methodologies
Experience with real-world smart meter data processing and analytics
Experience with CYME, OpenDSS, or similar distribution simulation packages
Experience with machine learning
Benefits
Medical, dental, and vision insurance
403(b) Employee Savings Plan with employer match*
Sick leave (where required by law)
Company
National Laboratory of the Rockies
The U.S. Department of Energy's primary national laboratory for energy systems research and development.
Funding
Current Stage
Late StageTotal Funding
$166.09MKey Investors
US Department of EnergyARPA-E
2024-09-04Grant
2023-09-21Grant· $1M
2023-05-22Grant· $150M
Recent News
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