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Concordia University

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Fully funded PhD in Digital Twins and Energy Systems for Low-Carbon Housing at Concordia University Concordia University in Canada

Degree Level

Master's, PhD

Field of study

Computer Science

Funding

Full funding available
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Country

Canada

University

Concordia University

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Keywords

Computer Science
Environmental Science
Mechanical Engineering
Electrical Engineering
Smart Grid Technology
Civil Engineering
Energy Engineering
Building Physics
Digital Twin Technology
Electricity
energy storage systems

About this position

Fully funded PhD opportunity at Concordia University in Montreal, Canada, focused on digital twins, energy systems, low-carbon housing, building energy simulation, retrofit strategies, electrification, and urban sustainability.

The position is part of the Volt-Age research environment and the Quebec Sustainable Social and Community Housing Living Lab, supervised by Professor Ursula Eicker. The project works on decarbonization and electrification in social, affordable, and low-income housing, with living-lab sites in Longueuil, Montreal-Nord, Hochelaga, and Montreal.

Research tasks include developing and implementing digital twin models for low-income housing and urban districts, building and applying building energy simulation models, designing retrofit strategies such as heat pumps, thermal storage, PV systems, and battery integration, modeling electrification scenarios, and contributing to decision-support tools for housing authorities and municipalities. The work also involves urban sustainability indicators, real-time monitoring data, and integration with 3D city models and the Tools4Cities platform.

Funding: fully funded PhD with tuition coverage and a competitive stipend; the post specifies 35K CAD per year for 4 years.

Eligibility highlights: master’s degree in Building Engineering, Mechanical Engineering, Energy Systems, Civil Engineering, or a related field; strong background in building physics and energy systems modeling; experience with EnergyPlus, TRNSYS, Modelica, or similar tools; programming in Python or MATLAB; and interest in sustainable cities and low-carbon infrastructure.

How to apply: send a single PDF to [email protected] including a letter of intent, CV, transcripts, referee contacts, and supporting documents. Use the email subject line Digital twins_Your name. Applications are reviewed on a rolling basis.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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