Senior Research Scientist – AI/ML for Energy Systems

Pacific Northwest National Laboratory

7d•Hybrid

About The Position

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus. The Energy and Environment Directorate delivers science and technology solutions for the nation’s biggest energy and environmental challenges. Our more than 1,700 staff support the Department of Energy (DOE), delivering on key DOE mission areas including: modernizing our nation’s power grid to maintain a reliable, affordable, secure, and resilient electricity delivery infrastructure; research, development, validation, and effective utilization of renewable energy and efficiency technologies that improve the affordability, reliability, resiliency, and security of the American energy system; and resolving complex issues in nuclear science, energy, and environmental management. The Electricity Infrastructure and Buildings Division, part of the Energy and Environment Directorate, is accelerating the transition to an efficient, resilient, and secure energy system through basic and applied research. We leverage a strong technical foundation in power and energy systems and advanced data analytics to drive innovation, transform markets, and shape energy policy. On-site in Richland or Seattle, WA is strongly preferred; remote work is considered.

Requirements

BS/BA and 7+ years of relevant work experience -OR-
MS/MA and 5+ years of relevant work experience -OR-
PhD with 3+ year of relevant experience
Must be able to acquire and maintain a national security clearance, Q/SCI.

Nice To Haves

Expertise in energy systems, power systems, or grid operations, with a strong understanding of the technical and operational challenges facing modern and future grids.
Understanding and experience applying machine learning and agentic approaches to the grid domain.
Experience integrating AI models, including Agentic approaches, into planning or real-time operations engineering workflows for electric utilities or ISOs/RTOs.
Experience in emerging AI applications, particularly around explainable AI, ethical AI, and AI for critical infrastructure.
Strong communication and technical writing skills with the ability to translate complex concepts into actionable insights for diverse audiences, including technical experts, policymakers, and stakeholders.
Developing professional network within AI, ML, DOE, or energy industry communities.
Experience in end-to-end research from problem formulation through validated prototypes, including datasets, hybrid AI methods, and benchmark metrics.

Responsibilities

Conduct and contribute to cutting-edge research applying AI, including generative AI, foundation models, and agent-based approaches, to improve the operation, planning, automation, resilience, and security of the electrical grid.
Develop approaches and applied solutions for forecasting, anomaly detection, grid disturbance identification, model validation, and human-in-the-loop decision support tools for operators.
Serve as the principal investigator (PI) on multi-disciplinary research projects funded by DOE, ARPA-E, utilities, and other stakeholders; define technical vision and milestones, build teams, manage deliverables, and oversee successful execution.
Collaborate with cross‑disciplinary teams by providing grid domain expertise to AI researchers in other areas.
Mentor and coach staff in the AI and grid research space, fostering a culture of innovation, growth, and excellence within the team.
Collaborate with internal and external stakeholders, including universities, grid operators, ISO/RTOs, other national labs, and solution providers, to identify emerging needs and develop solutions that scale to the real world.
Disseminate results through peer-reviewed publications, present research findings at conferences, and represent PNNL in the AI-for-energy community.

Benefits

Employees and their families are offered medical insurance, dental insurance, vision insurance, robust telehealth care options, several mental health benefits, free wellness coaching, health savings account, flexible spending accounts, basic life insurance, disability insurance, employee assistance program, business travel insurance, tuition assistance, relocation, backup childcare, legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support.
Employees are automatically enrolled in our company-funded pension plan and may enroll in our 401 (k) savings plan with company match.
Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

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