Develop graph-based inverse reinforcement learning and deep learning models as a Postdoctoral Fellow with the NRC in Hamilton. Work full-time onsite.
The National Research Council seeks a Postdoctoral Fellow for a two-year term in Automotive and Surface Transportation. You will analyze driver eye-gaze scanpaths under adverse weather, infer reward structures, and forecast gaze trajectories and driving actions. The work supports innovative research within a multidisciplinary team and includes participation in additional projects.
Key Responsibilities: Develop graph-based inverse reinforcement learning frameworks
Analyze and forecast human driver eye-gaze scanpaths
Apply spectral graph analysis to gaze patterns
Build deep learning prediction pipelines




Participate in multidisciplinary research projects
Requirements: PhD in Computer Engineering, Computer Science, or related field
Two to six years developing advanced deep learning architectures
Explicit, concise Python or C++ coding experience
Experience with PyTorch, TensorFlow, and machine learning libraries
English language proficiency and Reliability Status eligibility
Apply deep learning, graph analysis, and reinforcement learning expertise to driver attention research at the NRC.

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📌 Postdoctoral Fellow Deep Reinforcement Learning (Ontario)
🏢 The Institute for Performance and Learning
📍 Ontario