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PhD Student in Energy Management Systems (EMS), Battery Management Systems (BMS), MATLAB, Python

Montreal, Quebec, Canada
Entry Level
Full-Time

About the role

Fully Funded PhD Student in Energy Management Systems (EMS), Battery Management Systems (BMS), Python, MATLAB

Supervisor: Dr. Karim Zaghib, Department: Chemical and Materials Engineering, Gina Cody School of Engineering and Computer Science University: Concordia University, Montreal, Canada Start Date: Fall 2026 PhD fellowship: 35K CAD per year for 4 years

Project: Advancing Autonomous Energy Networks in the North: Research and Development of Technologies for Extreme Cold Environments Description: engineering/control systems project

PROJECT OVERVIEW

Northern Quebec communities continue to rely on diesel-based electricity, leading to high costs, greenhouse gas emissions, and limited energy independence. This research project aims to develop intelligent, cold-climate energy solutions by integrating advanced lithium-ion batteries, hydrogen fuel cells, renewable energy sources, and autonomous Energy Management Systems (EMS) for hybrid microgrids. The successful candidate will contribute to the design of intelligent energy management and battery management technologies that improve system reliability, efficiency, and resilience under Arctic conditions, supporting sustainable and energy-sovereign solutions for northern and Indigenous communities.

ROLE TASKS

Conduct research on intelligent Energy Management Systems (EMS) for autonomous hybrid microgrids operating in cold-climate environments. Design, develop, and optimize advanced Battery Management Systems (BMS/BMU) for lithium-ion battery technologies under extreme low-temperature conditions. Develop intelligent energy management algorithms for optimal coordination of battery storage, hydrogen fuel cells, solar PV, wind generation, and diesel backup systems. Design predictive control, optimization, and machine learning models to improve energy efficiency, reliability, and resilience of hybrid energy networks. Develop advanced battery state estimation algorithms, including State of Charge (SOC), State of Health (SOH), and Remaining Useful Life (RUL), accounting for nonlinear battery behavior in cold climates. Develop software and hardware prototypes of EMS and BMS architectures and validate their performance under simulated Arctic operating conditions. Analyze operational data to improve system performance, optimize charging and discharging strategies, and minimize energy losses. Support the development and validation of Vehicle-to-Everything (V2X) technologies, including bidirectional charging and vehicle-grid integration. Collaborate with multidisciplinary researchers in battery materials, hydrogen technologies, power electronics, renewable energy systems, and Indigenous energy initiatives. Publish research findings in high-impact peer-reviewed journals and present results at leading international conferences. Contribute to the development of next-generation autonomous energy systems that improve energy security, sustainability, and resilience for northern and Indigenous communities. REQUIREMENTS

Master's degree in Electrical Engineering, Energy Engineering, Computer Engineering, Mechatronics, Control Systems, Power Systems, or a closely related discipline. Strong background in Energy Management Systems (EMS), Battery Management Systems (BMS), renewable energy systems, microgrids, or battery energy storage systems. Experience developing optimization, control, or predictive algorithms for complex energy systems. Proficiency in programming using Python, MATLAB/Simulink, C/C++, or similar scientific computing environments. Knowledge of battery modeling, lithium-ion batteries, state estimation (SOC/SOH), electrochemical energy storage, or battery diagnostics. Experience with machine learning, artificial intelligence, optimization methods, or model predictive control is considered an asset. Familiarity with renewable energy integration, hydrogen energy systems, power electronics, or smart grid technologies is considered an asset. Experience with real-time simulation, embedded systems, hardware-in-the-loop (HIL), or digital twins is considered an asset. Strong analytical, problem-solving, and research skills, with the ability to work independently and collaboratively in multidisciplinary teams. Excellent written and verbal communication skills and demonstrated interest in publishing high-quality scientific research. Interest in sustainable energy systems, cold-climate technologies, and the development of resilient energy solutions for remote and Indigenous communities.

HOW TO APPLY

Please send the following documents in a single PDF file to volt-age.recruitment@concordia.ca: Letter of intent clearly aligned with the professor’s research domain (You may also review their recent publications and highlight relevant experience.) Academic CV Unofficial transcripts with CGPA and course names Names and emails of 3 referees Publications with embedded links, if any Any other supporting documents that strengthen your application

Subject of the email: EMS_Your Name

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