Researcher: Machine Learning/Artificial Intelligence Applications to Power Systems

Posting TitleResearcher: Machine Learning/Artificial Intelligence Applications to Power Systems

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LocationCO - Golden

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Position TypeRegular

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Hours Per Week40

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Working at NRELThe 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.

Join the National Renewable Energy Laboratory (NREL), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NREL stands out in the research community for its commitment to an affordable and secure energy future.  Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.

At NREL, you’ll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.

Learn about NREL’s critical objectives: NREL's Mission and Vision.

Job Description

The Grid Automation and Controls Group of the Power Systems and Engineering Center (PSEC) at NREL is looking for an exceptional researcher to support ongoing project work in the operation, control, modeling, and simulation of the power grid, while the power grid is transitioning to a low-carbon and high-renewable grid.

We are looking for a researcher who has solid background on machine learning with enough knowledge about power systems. The candidate will work on research projects that use machine learning (ML)/ artificial intelligence (AI) to solve power system problems, specially with the focus on Generative AI (GenAI) and Large Language Models (LLM). Ideal candidate is expected to have in-depth knowledge and extensive research experience related to GenAI and LLM, and can apply the AI knowledge to solve energy system problems. Ideal candidate should have solid programming skillset. Knowledge and experience about power systems is a plus. 

The ideal candidate should be able to conduct research work with limited guidance from senior researchers, and also collaborate with project PI and other power system researchers from the same project team. 

The researcher III is expected to work independently and contribute to collaborative projects with minimal oversight.

The researcher IV is expected to work independently and lead collaborative projects with minimal oversight. The Researcher IV may also be responsible for leading and providing strategic project direction

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Basic QualificationsRelevant PhD . Or, relevant Master's Degree and 3 or more years of experience . Or, relevant Bachelor's Degree and 5 or more years of experience . Demonstrates broad understanding and wide application of engineering technical procedures, principles, theories and concepts in the field. General knowledge of other related disciplines. Demonstrates leadership in one or more areas of team, task or project lead responsibilities. Demonstrated experience in management of projects. Very good writing, interpersonal and communication skills.
Relevant PhD and 4 or more years of experience . Or, relevant Master's Degree and 7 or more years of experience . Or, relevant Bachelor's Degree and 9 or more years of experience . Applies extensive engineering technical expertise, and has full knowledge of other related disciplines. Considered a technical resource. Demonstrates leadership in several areas of team, task or project lead responsibilities. Demonstrated experience in management of projects. Excellent writing, interpersonal and communication skills.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• Advanced degree in Electrical Engineering or Computer Science or related fields.
• Experience in one or more ML/AI techniques
• Strong programming skills
• Experience in natural language learning, generative AI, large language models, foundation models, etc.
• Strong fundamental knowledge of neural networks, state-of-the-art learning algorithms, and their applications to complex systems
• Python experience
• Experience with High Performance computing

Preferred Qualifications

• Familiar with power system modeling and power system optimization  
• Experience in using high performance computers and Linux systems
• Advanced research background in power systems, distribution grids, building and vehicle grid integrations
• Proficiency using Python and machine learning/reinforcement learning packages

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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: Researcher III / Annual Salary Range: $81,500 - $146,700

Job Profile: Researcher IV / Annual Salary Range: $97,800 - $176,000

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 SummaryBenefits include medical, dental, and vision insurance; short*- and long-term disability insurance; pension benefits*; 403(b) Employee Savings Plan with employer match*; life and accidental death and dismemberment (AD&D) insurance; personal time off (PTO) and sick leave; paid holidays; and tuition reimbursement*. 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. Limited-term positions are not eligible for long-term disability or tuition reimbursement.

* Based on eligibility rules

Badging RequirementNREL 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.

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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