CES Community Energy Solutions
Funded PhD position in Computer Science and Software Engineering
Last updated: September 10, 2025, 3:55 p.m.
Supervisory details
Supervisor: Yann-Gaël Guéhéneuc
Department: Computer Science and Software Engineering, Gina Cody School of Engineering and Computer Science
University: Concordia University, Montreal, Canada
Start date: Fall 2025, Winter 2026, Summer 2026
PhD Fellowship: 35K CAD per year for 4 years
Project overview
Community Energy Solutions (CES) accelerates decarbonization by empowering communities to co-design and monitor local energy systems using digital twins and participative methods. The project analyzes Canadian municipalities, tests innovative solutions through case studies, and scales best practices. CES integrates technical, economic, policy, and social perspectives to align local actions with national goals, supported by collaborations and data-sharing frameworks.
Role description
- Design and implement digital twin models representing energy consumers, producers, and distribution networks at the community scale.
- Develop graph and time-series data structures to represent heterogeneous building, mobility, and energy infrastructure data.
- Apply and integrate domain-specific algorithms for building and mobility demand, as well as energy supply, storage, and distribution.
- Parameterize algorithms based on case study data to generate accurate and context-specific results.
- Design and orchestrate workflows that combine demand models with system choice simulations.
- Define and apply a common data ontology to structure heterogeneous datasets based on community archetypes.
- Structure archetype catalogues for buildings (construction, usage, processes) and mobility-related loads across different climate zones.
- Automatically generate distribution network models to analyze:
- Voltage stability and congestion in electrical grids.
- Heat losses, pumping power, and storage integration in thermal networks.
- Create optimization workflows to select suitable energy solutions for community archetypes, considering multiple technical and operational options.
- Integrate detailed simulation models to refine solutions, including component sizing and optimal placement.
- Follow an agile, iterative development process, integrating feedback from archetype development and case study analysis.
- Opportunity to contribute to innovative research in digital twin technologies, data structuring, and optimization workflows for community energy systems.
- Access to state-of-the-art computing facilities, energy modelling platforms, and simulation tools at Concordia University.
- Supervision and mentorship from Professor Yann-Gaël Guéhéneuc, an internationally recognized expert in software engineering, modelling, and program analysis.
- Opportunities to publish in top-tier journals and conferences in software engineering, energy systems, and smart infrastructure.
- Competitive funding package, along with support for professional development, technical training, and networking with leading researchers, industry experts, and policymakers in sustainable energy and smart cities.
- Software development, modelling, comprehension
- Static, dynamic, and historical analyses
- Internet of Things
- Service-oriented architecture
- Bachelor’s or Master’s in Computer Science, Software Engineering, Energy Systems, or a related field.
- Strong background in software architecture, modelling, and data structuring.
- Experience with graph-based data models and time-series data analysis.
- Knowledge of digital twin technologies and their application to energy systems, mobility, or urban infrastructure.
- Familiarity with ontology development for heterogeneous datasets.
- Experience with algorithm integration for energy demand, supply, storage, or network analysis.
- Understanding of optimization methods and workflow orchestration for simulation-based decision-making.
- Programming proficiency in languages such as Python, Java, or C++, with experience in API development and data processing pipelines.
- Familiarity with energy distribution networks (electrical and/or thermal) and related simulation tools.
- Ability to work in an agile development environment with iterative feedback cycles.
- Strong analytical and communication skills, with the ability to collaborate in a multidisciplinary research team.
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
Test results
- Read the papers available here at and attach three reading notes as PDF file following the template provided at the same address.
- Download the code of our tool suite in Eclipse, compile it and run the class ProjectViewer in /Ptidej UI Viewer Standalone Swing/src/ptidej/viewer/ProjectViewer.java? (Please use this Github repository).
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 volt-age.recruitment@concordia.ca with the subject as:
CES_Your Name_MSc/PhD
Applications will be considered on a rolling basis.
Questions/contact
For all questions, please contact Alisa Makusheva at alisa.makusheva@concordia.ca.
