PhD in AI for Smart Energy Systems at Carleton University Carleton University in United States

Carleton University is recruiting a PhD student for research in AI for Smart Energy Systems.

The project focuses on applying Artificial Intelligence to smart energy systems such as microgrids and nanogrids. Research directions include Deep Reinforcement Learning (DRL), Multi-Agent Reinforcement Learning (MARL), Large Language Models (LLMs), and Agentic AI for optimal energy management, renewable energy integration, battery energy storage systems, electric vehicles, demand response, and cyber-physical resilient grid operation.

The position is being advertised by Shichao Liu, Associate Professor, P. Eng, at Carleton University in Ottawa, Canada. The post explicitly seeks a highly motivated PhD student to join the research group beginning in Fall 2026 or Spring 2027.

Eligible applicants should have a strong background in Electrical Engineering, Computer Engineering, Computer Science, Artificial Intelligence, Machine Learning, Control Systems, Power Systems, or a related field. Strong experience with Python, PyTorch/TensorFlow, reinforcement learning, optimization, or energy systems is highly desirable. Preference is given to candidates with prior research experience in reinforcement learning, multi-agent systems, LLMs, energy management systems, microgrids, or power and energy applications.

To apply, email the supervisor with your CV including publications and unofficial undergraduate and graduate transcripts. No formal deadline is stated in the post.