Postdoctoral Researcher: Machine Learning​/Artificial Intelligence to Power Systems

Posting Title

Postdoctoral Researcher:
Machine Learning/Artificial Intelligence Applications to Power Systems

CO - Golden

Postdoc (Fixed Term)

40

NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.

Join the National Laboratory of the Rockies (NLR), where world‑class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR 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 NLR, 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.

The Grid Automation and Controls Group of the Power Systems and Engineering Center (PSEC) at the National Laboratory of the Rockies (NLR) is looking for an exceptional Ph.D. graduate to support research 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.

Must be a recent PhD graduate within the last three years.

• Must meet educational requirements prior to employment start date.

• Relevant Ph.D. in Electrical Engineering or Computer Science or related fields.
• Experience in one or more ML/AI techniques.
• Strong programming skill.

• In‑depth knowledge in graph neural networks and reinforcement learning.
• Proven records of research experience related to power systems and power system optimization.
• Experience in natural language learning, generative AI, large language models, foundation models, etc.
• Have a good fundamental knowledge of neural networks, state‑of‑the‑art learning algorithms, and their applications to complex systems.
• Proficiency in using Python and machine learning/reinforcement learning packages.
• Experience in using high performance computers, Linux systems.
• With strong publication record.

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

Job Profile:
Postdoctoral Researcher / Annual Salary Range: $76,600 - $126,400

Benefits include medical, dental, and vision insurance; short‑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; and paid holidays. NLR 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…