Toronto Metropolitan University is offering fully funded PhD positions in the DECODER project, focusing on Building Information Modeling (BIM) Data Structures, Process Modeling, and Digital Twin Systems for Building Portfolio Assessment. The research is led by Professor Jenn McArthur in the Department of Architectural Science. The DECODER initiative aims to develop advanced digital tools for improving building energy performance and supporting large-scale decarbonization projects. The project bridges data science, building engineering, and sustainability to create scalable, intelligent solutions for building performance optimization. Two main PhD positions are available: (1) Developing Information Structures, which focuses on data exchange standards, process modeling, and openBIM/openGIS integration; and (2) Digital Twin for Portfolio Assessment, which involves automated geospatial data capture, AI-driven inference, and energy/cost simulation for retrofit scenarios. The work combines rapid energy modeling, fault detection and diagnostics, semantic learning, and self-tuning optimization algorithms to enhance operational efficiency and guide retrofit strategies. Applicants should have a master's degree in a relevant field such as civil/building engineering, architecture, geoinformatics, computer science, GIS, or mechanical engineering. Required skills include experience with openBIM, openGIS, process modeling, information workflows, data schema design, and strong programming and analytical skills. Familiarity with facility management data, building performance concepts, GIS platforms, spatial databases, and geospatial workflows is an asset. The positions are open to Canadian residents and citizens only. The PhD fellowship provides a stipend of 35,000 CAD per year for four years, supporting living expenses. The application process requires submission of a single PDF containing a letter of intent, academic CV, unofficial transcripts, names and contact information of two referees, publications (if any), and any other relevant documents. Applications should be sent to [email protected], with the position (WP1 or WP4) specified in the subject line. Applications are reviewed on a rolling basis. For more information, visit the DECODER project page or contact the project team. This opportunity is ideal for students interested in BIM, digital twins, smart building systems, energy simulation, retrofit optimization, and sustainable building design.

Professor Jenn McArthur at Toronto Metropolitan University is recruiting PhD candidates for her research group in Building Science, with a focus on building energy modeling, HVAC systems, energy management, and the application of machine learning and deep learning techniques. Two PhD positions are available: one for candidates with expertise in building energy modeling, thermodynamics, and heat transfer (especially in HVAC), and another for candidates with advanced deep learning skills to lead research on integrating learning into HVAC equipment emulators. The research involves developing retrofit decision-making tools and building emulator development using tuned archetypes and surrogate models. Applicants should have a strong background in relevant engineering fields, such as civil or mechanical engineering, and experience or willingness to learn machine learning. For the deep learning-focused position, a background in computer science, data science, or machine learning, combined with knowledge of building HVAC systems, is required. All studies are in-person in Toronto, and domestic applicants are strongly preferred, though exceptional international candidates will be considered. The group is committed to diversity and encourages applications from underrepresented groups, including BIPOC, women, LGBTQ+, and disabled students. First-generation PhD students or those needing accommodations are encouraged to reach out for support. All PhD students in the group receive a stipend of $35,000/year plus scholarships (from Fall 2026) to subsidize tuition. The application process requires submission of a cover letter, CV, unofficial transcripts from Bachelors and Masters degrees, a sample of academic writing, and contact details for two references, all combined into a single PDF and sent via email. The successful candidates will also need to complete the formal application process at Toronto Metropolitan University, with final acceptance determined by the admissions committee. Applications will be considered until the positions are filled, with a start date in Spring (May 2026) or Fall (September 2026). Key research areas include building science, HVAC, energy management, machine learning, deep learning, and emulator development. This is an excellent opportunity for students interested in the intersection of engineering, data science, and sustainable building technologies.