AI Researcher — Energy Systems & Scientific ML

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.

AI Researcher

CO - Golden

Limited Term (Fixed Term)

40

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 Computational Sciences Center (CSC) is seeking a researcher within the AI, Learning and Intelligent Systems (ALIS) group with a demonstrated track record of work at the intersection of AI and physical sciences. The researcher should be dynamic, motivated, and have a strong interest in advancing energy innovation at NLR.

In the CSC, we integrate discovery science, engineering, and mission delivery to translate breakthrough research into operational capabilities, with core strengths in high‑performance computing, AI/ML, modeling and simulation, and visualization. We steward state‑of‑the‑art supercomputing and data facilities, secure research environments (including classified spaces), and specialized testbeds that enable end‑to‑end development and red‑team evaluation. NLR collaborates across DOE program offices and with the defense and intelligence communities, other federal agencies, universities, and industry through public–private partnerships and technology transition pathways, while fostering a culture of scientific excellence, operational rigor, and responsible research.

We are seeking a researcher working at the intersection of machine learning and the physical sciences to develop AI-driven solutions for complex energy and environmental systems. This role emphasizes both technical depth and scientific leadership, with opportunities to shape new research directions and contribute to high-impact proposals.

• Conduct research in ML for scientific and engineering applications, including (but not limited to) generative modeling, spatiotemporal learning, operator learning, and AI-assisted scientific workflows
• Collaborate within multidisciplinary teams and engage domain experts to translate real-world challenges into tractable research problems
• Formulate novel research questions and lead the development of new technical directions
• Contribute to and help lead proposal development and strategic research initiatives
• Develop and evaluate AI methods for data-scarce, multi-scale, and complex physical systems

Candidates should have a strong technical background, good work ethic, experience in leadership and mentorship, and be comfortable learning and applying new technologies, as the role will include self-starting and performing technical tasks independently. The role also requires collaboration and effective communication with peers, mentors, and team members. The successful candidate will not shy away from tackling challenges, but rather, demonstrate eagerness to engineer creative solutions.

In this vein, the candidate should have a high degree of curiosity, excitement to work as a team, and ability to adapt to needs of differing projects and challenges by gaining and utilizing new skills in support of research goals.

Relevant PhD . Or, relevant Master's Degree and 3 or more years of experience . Or, relevant…