At Pacific Northwest National Laboratory (PNNL), we are solving some of the nation’s greatest energy challenges by delivering transformative research and scalable innovations. 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. This position is in the Building Simulation and Design Group (BS&DG) within PNNL’s Electricity Infrastructure and Buildings Division. BS&DG conducts modeling and analysis to evaluate the impacts of building energy policies, codes, and standards; develops tools and workflows to support building research and decision making; and helps accelerate adoption of energy efficient technologies. The group maintains core research capabilities in building energy simulation, building energy policy analysis, and tool development for building applications. BS&DG is seeking a Postdoctoral Research Associate – AI for Building Energy Systems. The successful candidate will be accountable to Project and/or Task Managers for performing assigned roles, following applicable project and field procedures, and completing assigned tasks on time and within budget. The candidate will also be accountable to the Group Leader and Team Leader for staff performance and development, operational discipline, and project execution. This position is based in Portland, OR, Richland, WA, or Seattle, WA and requires an onsite presence. Hybrid work arrangements may be available in accordance with laboratory policy, project needs, and team expectations. This role will support AI-enabled building energy systems research under DOE mission areas, with applications that may include building energy modeling, code compliance checking, permitting, large-scale performance data analysis, workflow automation, building controls and operations, workforce training, data mining, and AI-enabled software tools. The successful candidate will join multi-disciplinary project teams and contribute to research on AI methods, computational methods, and technical workflows for building research, analysis, and decision making, while growing toward increased technical independence. Conduct research in AI-enabled building energy systems research under a given mission area, including generative AI, large language models, and agentic systems for building research applications.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree