Karim Zaghib

Concordia University in Montreal, Canada is advertising a fully funded PhD position in Energy Storage Modelling and Intelligent Energy Management within the Volt-Age research environment. The project is supervised by Professor Karim Zaghib and is aimed at developing physics-based and data-driven models for battery charging, discharging, degradation, and lifecycle performance. The research focus includes battery management strategies , predictive modelling for battery degradation, state estimation (SOC/SOH) , lifecycle analysis under varying operating conditions, and the co-optimization of photovoltaic (PV) generation with battery energy storage systems . This opportunity is especially relevant for candidates interested in Electrical Engineering , Materials Science , Physics , Computer Science , and broader Energy/Sustainability research. The post states that the position is for Fall 2026 and includes a scholarship of 35K CAD per year for 4 years . This indicates a strong funding package for a doctoral student. The announcement is shared by Alisa Makusheva , who appears to be academic staff involved in recruiting MSc and PhD students for funded Volt-Age research projects at Concordia University. Applicants should review the full role description and application instructions using the provided link. If you are interested in battery modelling, intelligent energy management, renewable integration, or sustainable energy systems, this is a relevant funded PhD opening to consider.

Concordia University in Montreal, Quebec, Canada is advertising a fully funded PhD position in Energy Management Systems (EMS) and Battery Management Systems (BMS/BMU) for Fall 2026 . The project is associated with Professor Karim Zaghib and focuses on advanced research in lithium-ion battery technologies under extreme low-temperature conditions. The successful PhD student will work on intelligent energy management algorithms for coordinating battery storage , hydrogen fuel cells , solar PV , wind generation , and diesel backup systems . The research also includes predictive control , optimization , and machine learning models to improve energy efficiency, reliability, and resilience in hybrid energy networks. Another major component of the project is advanced battery state estimation, including State of Charge (SOC) , State of Health (SOH) , and Remaining Useful Life (RUL) , with attention to nonlinear battery behavior in cold climates. This makes the opportunity especially relevant for students interested in energy systems, battery analytics, and sustainable power technologies. Funding is clearly stated: 35K CAD per year for 4 years . The post describes the role as fully funded and provides a link to the full role description and application instructions. Interested applicants should review the linked posting and follow the application steps there. Questions about the position or application process can be directed to the poster.

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.

PhD opportunity at Concordia University in Explainable AI for Resilient Energy Optimization and Storage (EXAIREOS) , part of the Volt-Age Living Lab. The project is supervised by Prof. Karim Zaghib in the Department of Chemical and Materials Engineering at Concordia University, Montreal, Canada. It focuses on battery energy storage , renewable energy integration , solar energy systems , energy management , and explainable artificial intelligence (XAI) for building energy optimization and decarbonization. Research topics include battery modeling and optimization, battery degradation and lifecycle analysis, state estimation (SOC/SOH), photovoltaic-battery co-optimization, renewable forecasting, intelligent energy management, and AI-powered simulation and decision-support tools. The successful candidate will work with real building energy data, weather data, electricity tariffs, and renewable generation profiles, and will collaborate with multidisciplinary researchers and industry partner Énergère. Funding: fully funded PhD with tuition coverage and a competitive stipend of CAD 35,000 per year for 4 years . Eligibility: applicants should have a master's degree in a relevant engineering or closely related field, with strong preparation in battery systems, renewable energy, modeling/simulation, optimization, Python or MATLAB/Simulink, and preferably machine learning or XAI. Start date: Fall 2026. Applications: rolling review. How to apply: send a single PDF with letter of intent, CV, unofficial transcripts, referee names/emails, publications, and supporting documents to [email protected] . Use the subject line EMS_Your name .