Posting Title

Research Engineer - Machine learning applications to power system operations

.

Location

CO - Golden

.

Position Type

Regular

.

Hours Per Week

40

.

Working at NLR

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.

Job Description

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

.

Basic Qualifications

For a Researcher II:
Relevant Master's Degree . Or, relevant Bachelor's Degree and 2 or more years of experience . General knowledge and application of engineering technical standards, principles, theories, concepts and techniques. Training in team, task or project leadership responsibilities. Intermediate abilities and knowledge of practices and techniques. Beginning experience in project management. Good writing, interpersonal and communication skills.
For a Researcher III:
Relevant 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.

* Must meet educational requirements prior to employment start date.

Additional Required Qualifications

• Must have a MS in computer science, electrical engineering, computer engineering or related fields. Must meet educational requirements prior to employment start date.
• Experience in natural language learning, generative AI, large language models, foundation models, etc.
• Strong programming skill
• Experience in using high performance computers, Linux systems

Preferred Qualifications

• In-depth knowledge in graph neural networks and reinforcement learning
• Proven records of research experience related to power systems and power system optimization  
• 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
• With strong publication record

.

Job Application Submission Window

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