Research Engineer III — Building Energy Modeling

Pacific Northwest National Laboratory•Portland, OR

4d•Hybrid

About The Position

The Research Engineer III will serve as a technical lead in the Building Simulation and Design Group within Pacific Northwest National Laboratory’s Electricity Infrastructure and Buildings Division. The group conducts modeling and analysis of building energy policies, codes, and standards; develops tools and workflows for building research and decision-making; and supports adoption of energy-efficient technologies. The role focuses on evaluating building energy performance, technologies, and efficiency policies through building energy modeling and analysis, with an emphasis on advanced EnergyPlus expertise, programming, data analysis, and integrating AI-enabled methods in accurate, reproducible, and practical workflows. The successful candidate will define research questions and technical approaches, lead simulation studies and major technical tasks or moderate projects, develop and improve modeling tools and workflows, guide contributors, and ensure the quality of research results. The position also involves working with sponsors and stakeholders, communicating findings and limitations, mentoring junior staff, producing technical reports and publications, contributing to proposals and funding opportunities, and collaborating across teams. The candidate is accountable to Project and/or Task Managers, the Group Leader, and the Team Leader for assigned responsibilities, project execution, professional development, operational discipline, and compliance with applicable procedures and expectations. The position may be based at a PNNL office in Portland, Oregon; Richland, Washington; or Seattle, Washington. On-site presence is expected. Hybrid arrangements may be available according to laboratory policy, project needs, and team expectations; remote work may be considered for candidates with strong technical expertise and demonstrated success working remotely.

Requirements

Bachelor’s degree in mechanical engineering, architectural engineering, building science, or a related technical field, and 5 years of relevant programming and data analysis experience; or a master’s degree in one of these fields and 3 years of relevant experience; or a Ph.D. in one of these fields and 1 year of relevant experience.
Advanced proficiency in EnergyPlus or OpenStudio-based building energy modeling.
Experience independently developing technical approaches and leading technical tasks.
Strong knowledge of building energy systems, advanced hands-on EnergyPlus modeling expertise, programming, and data analysis skills.
Demonstrated ability to lead technical work.
Applicants are strongly encouraged to submit a full academic or research CV.

Nice To Haves

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 EnergyPlus proficiency, including independently developing and modifying models of building envelopes, 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, and 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; high-performance or cloud computing experience 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; 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.

Responsibilities

Define research questions and select or develop modeling and analytical approaches, including methods, assumptions, evaluation metrics, and study boundaries.
Develop, modify, and troubleshoot EnergyPlus models covering building envelopes, HVAC, water heating, lighting, plug loads, controls, and operating schedules.
Design and lead simulation studies of building technologies, control strategies, codes, and standards, including parametric, sensitivity, and uncertainty analyses as appropriate.
Develop and improve 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.
Establish model verification and results-review procedures; investigate simulation errors and unexpected behavior; and assess physical consistency using engineering principles, reference cases, and measured data where available.
Collaborate with specialists to integrate and evaluate AI-enabled tools and methods for building modeling, data analysis, and workflow automation, documenting accuracy, limitations, and reproducibility.
Lead major technical tasks or moderate projects; coordinate contributors; and manage assigned scope, schedule, budget, technical quality, and deliverables.
Work with sponsors, collaborators, and stakeholders to understand research needs, develop technical approaches, and communicate progress, findings, and limitations.
Mentor junior staff and review models, analytical methods, code, and technical products developed by team members.
Lead development of technical reports, journal articles, and conference presentations; represent project work in sponsor meetings and technical forums.
Generate research ideas, develop funding opportunities with project teams, and lead technical sections of proposals.
Collaborate across the group and division to share methods, strengthen research capabilities, and identify related research opportunities.
Remain accountable 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, and quality, safety, and security expectations.