The Government of Quebec has set a target of 1 million Electric Vehicles (EVs) by 2030. In fact, Quebec will ban the sales of new gasoline-powered passenger cars by 2035. However, EV integration will lead to a high demand for charging spaces and power. Currently, there is a lack of both a reservation and a check-in system for EV owners to charge their cars at public charging stations (CSs) which may lead to uncertainty and could lead to reluctance in adoption by potential EVs’ owners. For operators, the lack of information (and tools to assess performance) would lead to uncertainty in infrastructure deployment and sizing existing ones to meet demands and maintain quality of service (QoS). In addition, there are several concerns among EVs owners including the driving range anxiety and the need to frequently charge their EVs. Further, the deployed public charging network may remain underutilized due to users’ hesitation caused by the desire to avoid long waiting times. Therefore, characterizing the average waiting time, improving utilization of the charging network, and large-scale deployment of EV infrastructure are indispensable components that should be addressed to improve the QoS for the charging network.

PhD in Electrical Engineering or Computer Science with strong background in Queuing theory and simulations, modeling, Machine leaning and Data analytics. A strong publication record and experience in co-mentoring graduate students is required.

Horizon position is expected to be filled as soon as possible but no later than March 1, 2024.

• All documents must be submitted to Chadi Assi
• Please include the reference number with your application

• One to three (1-3) page research statement demonstrating fit with the program described above 
• Current curriculum vitae demonstrating research excellence and a capacity for leadership in the domain (maximum 5 pages)
• Two letters of reference from academic supervisors or current employers to be sent via e-mail directly to: Chadi Assi