Post Doctoral Research Associate – AI Building Energy Systems

Overview

At Pacific Northwest National Laboratory (PNNL), the Electricity Infrastructure and Buildings Division within the Energy and Environment Directorate is accelerating the transition to an efficient, resilient, and secure energy system through basic and applied research. The Division leverages a strong technical foundation in power and energy systems and advanced data analytics to drive innovation, transform markets, and shape energy policy.

The Division’s Building Simulation and Design Group (BS&DG) performs 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. This position is a Postdoctoral Research Associate – AI for Building Energy Systems, based in Portland, OR, Richland, WA, or Seattle, WA.

The role will support AI‑enabled building energy systems research under DOE mission areas, including 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.

• Conduct research in AI‑enabled building energy systems under a given mission area, including generative AI, large language models, and agentic systems for building research applications.
• Develop and apply generative AI, large language model, and agentic methods for building research applications, including support for data preparation, testing, and technical evaluation.
• Develop and support analysis methods, modeling workflows, tools, and prototypes for building research applications under guidance from project leads.
• Contribute to technical products, analyses, and research outputs that support building research and decision making.
• Contribute to existing building research and engineering projects in these application areas, including projects with established workflows and projects transitioning toward AI‑enabled approaches.
• Execute assigned technical tasks and deliver high‑quality work within defined scope, schedule, and project expectations.
• Work with project teams and collaborators to support technical tasks and respond to project needs.
• Work effectively within interdisciplinary teams and collaborate closely with mentors, project leads, and teammates.
• Support proposal development through technical analysis, literature review, or background research.
• Contribute to technical reports, publications, and presentations related to assigned research.
• Stay current with relevant literature, methods, and tools in support of assigned research and professional growth.

Applicants are strongly encouraged to submit a full academic or research CV.

• Candidates must have received a PhD within the past five years (60 months) or within the next 8 months from an accredited college or university.

• PhD in architectural engineering, building science, mechanical engineering, or a closely related field, with strong potential to conduct independent research.
• Experience conducting building energy system analyses, such as modeling, controls analysis, or system performance evaluation.
• Experience developing or experimenting with AI or machine learning methods in engineering or scientific research applications.
• Experience programming in Python or similar languages to support modeling, simulation, or research data analysis.
• Experience contributing to research projects and delivering technical work within defined project scope and schedule.
• Experience supporting proposal preparation, such as technical analysis or background research.
• Record of technical publications or research contributions from doctoral research.
• Experience communicating research results through presentations or publications.

Not Applicable

This is not a Testing Designated Position (TDP).

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