Research Engineer III - Building Energy Modeling

Responsibilities

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.

The BS&DG is seeking a Research Engineer III - Building Energy Modeling with strong knowledge of building energy systems, advanced hands-on EnergyPlus modeling expertise, programming and data analysis skills, and demonstrated ability to lead technical work. The selected candidate will serve as a technical lead. They will select and develop technical approaches and lead research to evaluate building energy performance, building technologies, and energy efficiency policies, codes, and standards. Responsibilities include developing and improving modeling tools and simulation workflows, guiding technical contributors, ensuring the technical quality of research results, and communicating findings to sponsors and stakeholders. The candidate will also integrate AI-enabled methods into modeling and analysis workflows, with an emphasis on engineering accuracy, reproducibility, and practical value.

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 their own staff performance and development, operational discipline, and project execution.

The successful candidate will be responsible for:

• Defining research questions and selecting and developing modeling and analytical approaches to address building performance challenges, including appropriate methods, assumptions, evaluation metrics, and study boundaries.
• Developing, modifying, and troubleshooting Energy Plus models, representing the building envelope, HVAC, water heating, lighting, plug loads, controls, and operating schedules.
• Designing and leading simulation studies to evaluate building technologies, control strategies, codes, and standards, including parametric, sensitivity, and uncertainty analyses as appropriate.
• Developing and improving tools and reproducible workflows for large-scale building simulation, including automated model generation, batch or parallel execution, model and data management, quality checks, and results analysis across building types, climate zones, and analysis scenarios.
• Establishing model verification and results-review procedures, investigating simulation errors and unexpected behavior, and assessing physical consistency using engineering principles, reference cases, and measured data where available.
• Collaborating with relevant specialists to integrate and evaluate AI-enabled tools and methods for building modeling, data analysis, and workflow automation, including documenting accuracy, limitations, and reproducibility.
• Leading major technical tasks or moderate projects, coordinating contributors, and managing assigned scope, schedule, budget, technical quality, and deliverables.
• Working with sponsors, collaborators, and stakeholders to understand research needs, translate those needs into technical approaches, and communicate progress, findings, and limitations.
• Mentoring junior staff and reviewing models, analytical methods, code, and technical products developed by team members.
• Leading the development of technical reports, journal articles, and conference presentations, and representing project work in sponsor meetings and technical forums.
• Generating research ideas, developing funding opportunities with project teams, and leading technical sections of proposals.
• Collaborating across the group and division to share methods, strengthen research capabilities, and identify opportunities for related research.
• Maintaining accountability to Project and/or Task Managers, the Group Leader, and the Team Leader for assigned responsibilities, project execution, professional development, and operational discipline, including compliance with applicable procedures, training requirements, and quality, safety, and security expectations.

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

This position be based at a PNNL office in Portland, OR, Richland, WA, or Seattle, WA, with an on-site presence expected. Hybrid work arrangements may be available in accordance with laboratory policy, project needs, and team expectations. Remote work may be considered for candidates with strong technical expertise and demonstrated success working remotely.

Qualifications

Minimum Qualifications:

• BS/BA in mechanical engineering, architectural engineering, building science, or a related technical field, and 5 years of relevant programming and data analysis skills -OR-
• MS/MA in mechanical engineering, architectural engineering, building science, or a related technical field, and 3 years of relevant programming and data analysis skills -OR-
• PhD in mechanical engineering, architectural engineering, building science, or a related technical field, and 1 year of relevant programming and data analysis skills
• Advanced proficiency in EnergyPlus or OpenStudio-based building energy modeling
• Experience independently developing technical approaches and leading technical tasks

Preferred Qualifications:

• Graduate degree in architectural engineering, building science, mechanical engineering, or a closely related field with at least four years of relevant experience and demonstrated technical leadership and independent judgment in building energy research.
• Advanced, hands-on proficiency in EnergyPlus, including independently developing and modifying models of building envelope, air infiltration, HVAC, water heating, lighting, plug loads, controls, and operating schedules; diagnosing complex simulation errors; and evaluating results using building science and engineering principles.
• Strong programming and data analysis skills, preferably using Python, with experience developing reusable tools and automated workflows for model preparation, simulation execution, quality assurance, and results processing.
• Experience with version control, testing, code review, and documentation for collaborative research software development.
• Experience developing or improving large-scale building simulation workflows, including automated model generation, batch or parallel execution, model and dataset management, and quality assurance across building types, climate zones, or analysis scenarios. Experience with high-performance or cloud computing is a plus.
• Demonstrated ability to design simulation studies, assess assumptions and limitations, conduct sensitivity or uncertainty analyses, and establish technical checks for accuracy, physical consistency, and reproducibility.
• Experience evaluating building energy codes, standards, technologies, or control strategies using simulation, including developing representative models and interpreting results for research or policy applications.
• Experience applying and evaluating AI-enabled tools or methods for building energy modeling, data analysis, or engineering workflow automation is strongly preferred. Experience developing AI or machine learning methods, including surrogate models, is a plus.
• Demonstrated experience leading technical tasks or projects, coordinating contributors, and delivering technically sound results within assigned scope, schedule, and budget.
• Experience mentoring junior researchers and reviewing technical work developed by others.
• Strong written and verbal communication skills, with a record of leading technical reports, publications, or presentations; contributing research ideas and technical sections to proposals; and communicating effectively with sponsors, collaborators, and interdisciplinary teams.

Additional Information

Not Applicable.

Testing Designated Position

This is not a Testing Designated Position (TDP).