Job Description

The Energy Systems Control and Optimization group at NREL is looking for a summer PhD intern to join our research team to work on Autonomous Energy Systems project. Learn more here. The intern will be part of the Energy Systems Control and Optimization group under the Power Systems Engineering Center (PSEC) at NREL. PSEC supports the science and technology goals of the U.S. Department of Energy and NREL toward a sustainable energy future. The center works with the electricity industry to optimize strategies for effectively interconnecting renewable resources and emerging energy efficiency technologies in the existing power system. The center focuses on resolving grid integration barriers and providing improved control and management strategies for increased grid flexibility, consumer empowerment, and transportation electrification.

The successful candidate will work towards the development of scalable, distributed, and data-driven optimization algorithms for power systems.

The ideal candidate has experience in optimization theory or machine learning, preferably with applications to power systems.  The candidate should demonstrate experience in theory and algorithms development and basic programming skills.

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Basic Qualifications

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.

Please Note:
• Applicants are responsible for uploading 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.
• Must meet educational requirements prior to employment start date.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

The candidate should have a bachelor’s degree and should be studying for a PhD degree in Electrical Engineering, Computer Science, Mathematics or other systems engineering fields. In addition, the candidate should have knowledge of Julia and extensive working experience with PowerModelsONM.

Preferred Qualifications

Ideal candidates will have a background and expertise in one or more of the following topics:

• Convex optimization
• Machine learning
• Distributed solution methods for convex and/or nonconvex programs
• Demonstrates broad understanding and wide application of principles, theories, and concepts in operations, controls, and optimization of power systems
• General knowledge of other related disciplines
• Proficiency in one or more of the following programming languages: C, C++, Python, Matlab

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Job Application Submission Window

The anticipated closing window for application submission is up to 30 days and may be extended as needed.

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

Job Profile: / Annual Salary Range: $50,200 - $80,300

NREL takes into consideration a candidate’s education, training, and experience, 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.

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

Badging Requirement

NREL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.

Drug Free Workplace

NREL is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.

If you are offered employment at NREL, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.

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.

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Equal Opportunity 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, domestic partner 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.

Reasonable Accommodations

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