DECODER: Digitalization for Energy-Efficiency Through Commissioning and Decarbonization Retrofits
Funded MSc Scholarship in Building, Civil, and Environmental Engineering
Last updated: November 3, 2025, 9:36 a.m.
Supervisory details
Supervisor: Ursula Eicker
Department: Building, Civil, and Environmental Engineering, Gina Cody School of Engineering and Computer Science
University: Concordia University, Montreal, Canada
Start date: Winter 2026, Summer 2026
MSc Scholarship: 22K CAD per year for 2 years
Project overview
This project supports Canada’s efforts to reduce building-related emissions. It’s developing an AI-powered tool that helps building owners make better energy decisions. The system uses digital simulations to find the best ways to improve existing buildings—like upgrading heating systems or using smarter energy controls. It can also guide decisions across entire groups of buildings to save energy and cut emissions at scale.
Role description
- Expand and integrate the 3D Tools4Cities modeling framework to include enriched geometry and usage data for large building portfolios in Montreal, Toronto and other case studies.
- Develop tools and workflows to model retrofit scenarios for large building portfolios, assessing potential energy savings, costs, and emissions reductions.
- Define and implement retrofit suitability criteria (e.g., HVAC upgrades, envelope retrofits, fuel switching, controls optimization) using quantitative ranking methods such as AHP/ANP.
- Leverage and integrate outputs from BIM automation projects to generate enriched models for envelope and mechanical system retrofits.
- Build portfolio modeling workflows that allow parameter modification based on specific building knowledge and automate archetype-based default data generation.
- Apply AI-based data gap filling techniques (e.g., window-to-wall ratio estimation, function/usage derivation from proxies).
- Develop retrofit selection workflows that prioritize interventions based on building attributes, location- specific emission factors, and cost data.
- Conduct lifecycle carbon and cost assessments, generate retrofit scenarios, and analyze potential business models for portfolio-scale retrofits.
- Integrate co-benefits assessment into workflows, incorporating livability indicators such as accessibility, green space, public space design, and resilience to extreme weather.
- Automate the creation of ESG scorecards and environmental rating certificates (LEED, WELL, BOMA, etc.) for retrofit projects.
- Validate retrofit prioritization workflows with portfolio owners, adjusting weighting factors and criteria to align with economic, environmental, and social goals.
- Prepare research outputs for publication in top-tier journals and conferences and contribute to DECODER platform deliverables.
- Opportunity to contribute to innovative research in urban energy systems, large-scale building retrofit planning, and digital twin technologies within the DECODER platform.
- Access to cutting-edge urban simulation tools, 3D city modeling frameworks, and high-performance computing resources at Concordia University.
- Supervision and mentorship from Professor Ursula Eicker, a leading expert in zero-carbon cities, renewable energy integration, and urban-scale building performance modeling, with extensive international collaborations.
- Opportunities to publish in top-tier journals in urban sustainability, energy systems, and building performance and to present at leading international conferences.
- Competitive funding package, along with support for professional development, technical training, and networking with global experts, industry leaders, and policy makers in sustainable urban development.
- Urban energy systems
- 3D City modeling
- Urban data and simulation platform development
- Renewable energies
- Zero Carbon Cities
- Demand response and flexibility
- District and solar heating and cooling networks
- Sustainable transport
- Bachelor’s in Building Engineering, Architectural Engineering, Mechanical Engineering, Computer Science, or a related field.
- Strong knowledge of urban energy systems, building performance modeling, and retrofit planning.
- Experience with 3D modeling and data integration at building and urban scales (e.g., BIM, CityGML, GIS).
- Understanding of building archetypes, construction attributes, and retrofit measures, including HVAC systems, building envelope, and controls.
- Skills in multi-criteria decision-making methods (AHP/ANP) and lifecycle carbon/cost analysis.
- Experience in scenario modeling and business case development for building retrofits.
- Familiarity with livability and sustainability assessment frameworks (e.g., LEED, WELL, BOMA) and ESG reporting.
- Programming skills in Python for workflow automation and data processing are an asset.
- Ability to work with large and diverse datasets, applying AI or statistical methods to close data gaps.
- Strong communication skills in English, with the ability to present findings to both academic and industry audiences.
Please combine the following documents into a single PDF file.
- Letter of intent strongly aligned with the project and the research domain of the professor
- Academic CV
- Transcripts
- Names and contact information of 3 referees
- Publications, if any
- Test results (see below)
Test results
- Please check the test preparation guide before starting the test.
- Submit the quiz: Pandas + GeoPandas: Building Energy Dataset
- Passing score: 9/13.
- Take a screenshot of your result at the end of the test.
Applications must be in screen-readable PDF or Word formats.
If you are already in Canada, or if you’re a Canadian citizen or Permanent Resident, please highlight this in your communications.
Send your PDF file to alisa.makusheva@concordia.ca with the subject as:
DECODER_Your Name_MSc
Open until filled (applications will be considered on a rolling basis).
Questions/contact
For all questions, please contact Alisa Makusheva at alisa.makusheva@concordia.ca.
