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National Renewable Energy Laboratory Summer Graduate Internship: Machine-Learning for Power System Operation in Golden, Colorado

Posting Title

Summer Graduate Internship: Machine-Learning for Power System Operation



CO - Golden


Position Type

Intern (Fixed Term)


Hours Per Week



Annual Salary Range (based on full-time 40 hours per week)

Annual Salary Range: $39,600 - $63,500

Offers will typically be made in the bottom half of the listed range. NREL takes into consideration a candidate’s education, training, and experience, as well as the position's work location, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee’s salary history will not be used in compensation decisions.

Job Description

The National Renewable Energy Laboratory (NREL), located at the foothills of the Rocky Mountains in Golden, Colorado, is the nation’s primary laboratory for research and development of renewable energy and energy efficiency technologies. Successful candidates will join the Grid-connected Energy systems Modeling (GEM) group in the Power Systems Engineering Center (PSEC) at NREL, a highly interdisciplinary and collaborative team of engineers, analysts, and software developers working to develop and apply state-of-the art energy system modeling techniques, software, and simulations for breakthrough engineering and techno-economic analysis of the emerging future electric grid and broader interconnected energy system: transportation, buildings, gas, communication/controls, and beyond. PSEC supports the science and technology goals of the U.S. Department of Energy, NREL, and industry partners toward a sustainable energy future. The center works with the electricity industry and broader research community to conduct high-impact research and development that provides practical solutions to grid integration challenges that enable sustainable energy systems. PSEC uniquely combines the most advanced research techniques with real-world experience for achieving sustainable electricity grids.

NREL’s intern program provides a diverse opportunity for students and recent graduates. In addition to mentorship and real, hands-on experience, students and recent graduates will participate in professional development activities that will help strengthen their technical and professional skills.

The Grid-connected Energy systems Modeling (GEM) group at NREL is seeking a summer intern on machine-learning for power system operation simulations. Successful candidates will work on multi-timescale power system operations with large quantities of renewables. Specifically, they will work closely with NREL research engineers to perform/analyze power system studies across multiple time-scales (from millisecond-level electromechanical study to year-long production cost study). And then apply state-of-the-art machine-learning algorithms to address the challenges of high renewable energy penetration on power system operations. It is expected that this internship will be entirely remote. NREL will provide computing support, onboarding, web-based meetings and activities to enable a strong connection with the NREL and co-workers despite the virtual working environment.

The ideal candidate should have a good knowledge of machine-learning algorithms and power system operations.

Job Duties and Responsibilities:

  • Develop and implement machine learning models for power system stability assessment.

  • Prepare and Perform power system simulations.

  • Analyze power system operation and simulation data.

  • Publish results in top technical journals/conference proceedings.

  • Work closely and in collaboration with a diverse technical team.


Basic Qualifications

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. Internship period cannot exceed 12 months past graduation. Minimum of a 3.0 cumulative grade point average.

Please Note:

•You will need to upload official or unofficial school transcripts as part of the application process.

•If selected for position, a letter of recommendation will be required as part of the hiring process.


Additional Required Qualifications

  • General knowledge and application of power system operation and machine learning.

Preferred Qualifications

  • Experience with power system simulation software such as PSSE, PowerWorld or PSLF.

  • Experience with modeling of renewable energy resources.

  • Experience with machine learning or data analysis in Python, MATLAB or R

  • Experience with collaborative software development projects including version control. Quality documentation, and integrated testing support.

  • Excellent writing, interpersonal, and communication skills

Preferred Qualifications


Benefits Summary

Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NREL employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.

* Based on eligibility rules

Submission Guidelines

Please note that in order to be considered an applicant for any position at NREL you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.


EEO Policy

NREL is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

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The National Renewable Energy Laboratory (NREL) is a leader in the U.S. Department of Energy’s effort to secure an environmentally and economically sustainable energy future. With locations in Golden and Boulder, Colorado, and a satellite office in Washington, D.C., NREL is the primary laboratory for research, development, and deployment of renewable energy technologies in the United States.

NREL is subject to Department of Energy (DOE) access restrictions. All candidates must be authorized to access the facility per DOE rules and guidance within a reasonable time frame for the specified position in order to be considered for an interview. DOE rules for site access during the interview process are the same regardless of whether the candidate is interviewed on-site, off-site, or via telephone or videoconference. Additionally, DOE contractor employees are prohibited from participating in certain Foreign Government Talent Recruitment Programs (FGTRPs). If a candidate is currently participating in an FGTRP, they will be required to disclose their participation after receiving an offer of employment and may be required to disengage from participation in the FGTRP prior to commencing employment. Any offer of employment is conditional on the ability to obtain work authorization and to be granted access to NREL by the Department of Energy (DOE). We understand that COVID-19 may have caused delays or closures at offices, consulates, and embassies. However, NREL cannot make exceptions to work authorization and access requirements, and exceptions to these requirements are not being made for COVID-19 related delays.

Please review the information on our Hiring Process ( website before you create an account and apply for a job. We also hope you will learn more about NREL ( , visit our Careers site ( , and continue to search for job opportunities ( at the lab.