AI Researcher

National Laboratory of the Rockies•Golden, CO

1d•Onsite

About The Position

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.

Requirements

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 complete understanding and wide application of scientific 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 technical writing, interpersonal and communication skills.
Must meet educational requirements prior to employment start date.
Experience applying machine learning to real-world scientific or engineering problems (e.g., energy systems, remote sensing, or related domains)
Familiarity with modern ML approaches such as generative models, foundation models, or physics-informed/structured learning methods
Demonstrated ability to work across disciplines and drive research from concept to impact
Strong communication skills and a proactive, question-driven approach to collaboration
Demonstrated experience in leveraging high-performance computing

Nice To Haves

Demonstrated programming experience in C/C++, Java, Python, and using ML frameworks such as Pytorch and Tensorflow
Research experience in foundation models and/or large language models and/or agentic AI frameworks
Experience with writing proposals for research funding

Responsibilities

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