Karim Zaghib
2 months ago
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Fully Funded PhD in Autonomous Energy Networks, EMS, BMS, and V2X at Concordia University Concordia University in Canada
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD with tuition coverage and a competitive stipend. The post states a fellowship of 35,000 CAD per year for 4 years.
Country
Canada
University
Concordia University

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About this position
Fully funded PhD opportunity at Concordia University (Volt-Age) in Autonomous Energy Networks in the North, focused on energy management systems (EMS), battery management systems (BMS), vehicle-to-everything (V2X), hybrid microgrids, and cold-climate energy solutions.
The project is supervised by Prof. Karim Zaghib in the Department of Chemical and Materials Engineering, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, Canada. The research aims to develop intelligent, autonomous energy systems for northern Quebec and Indigenous communities, integrating lithium-ion batteries, hydrogen fuel cells, renewable energy sources, and predictive control/optimization methods for resilient off-grid and hybrid microgrids.
Research topics include: EMS design and optimization, BMS/BMU development, battery state estimation (SOC, SOH, RUL), machine learning and predictive control, renewable integration, hydrogen energy systems, power electronics, smart grids, real-time simulation, embedded systems, HIL, digital twins, and V2X/bidirectional charging.
Funding: fully funded PhD with tuition coverage and a competitive stipend. The post specifies 35,000 CAD per year for 4 years.
Eligibility highlights: applicants should hold a master's degree in a relevant engineering or closely related field and have a strong background in EMS/BMS, microgrids, renewable energy, battery systems, optimization/control, and programming (Python, MATLAB/Simulink, C/C++). Experience with AI/ML, battery modeling, hydrogen systems, or smart grids is an asset.
How to apply: send a single PDF by email to [email protected] including a letter of intent aligned with the professor’s research, academic CV, unofficial transcripts with CGPA and course names, names and emails of 3 referees, publications with embedded links if any, and any other supporting documents. Use the subject line EMS_Your name. Applications are reviewed on a rolling basis.
Start date: Fall 2026.
Funding details
Fully funded PhD with tuition coverage and a competitive stipend. The post states a fellowship of 35,000 CAD per year for 4 years.
What's required
Master's degree in Electrical Engineering, Energy Engineering, Computer Engineering, Mechatronics, Control Systems, Power Systems, or a closely related discipline. Strong background in EMS, BMS, renewable energy systems, microgrids, or battery energy storage systems. Experience developing optimization, control, or predictive algorithms for complex energy systems. Proficiency in Python, MATLAB/Simulink, C/C++, or similar scientific computing environments. Knowledge of battery modeling, lithium-ion batteries, SOC/SOH estimation, electrochemical energy storage, or battery diagnostics is preferred. Experience with machine learning, AI, optimization methods, model predictive control, renewable energy integration, hydrogen energy systems, power electronics, smart grids, real-time simulation, embedded systems, HIL, or digital twins is an asset. Strong analytical, problem-solving, research, and communication skills, plus interest in publishing high-quality research and working in multidisciplinary teams.
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