MSc and PhD Positions in Computer Vision, Cognitive Science, and Driving Simulator Research at University of Guelph University of Guelph in Canada

University of Guelph Assistant Professor Iuliia (Yulia) Kotseruba is advertising MSc and PhD positions in her lab, with starting dates in September 2026 and January 2027. The research is centered on computer vision, cognitive science, robotics, and AI, with two main directions: (1) cognitively-inspired computer vision systems for traffic scene analysis and modeling the behavior of drivers and pedestrians; and (2) driving simulator research, including human data collection and improving simulator fidelity.

The lab’s broader research interests include pedestrian behavior understanding, driver attention, cognitive architectures, human-centered traffic safety, and intelligent transportation. This is a strong fit for students interested in human-compliant models, behavioral data analysis, and real-world applications in autonomous and assistive driving.

Eligibility highlights: applicants should have a BSc or MSc in Computer Science or a related field, strong Python skills, and a genuine interest in research and learning new problems. Helpful background includes computer vision, cognitive science, data analysis (pandas/R), graphics/Unity, hardware/drivers, and machine learning frameworks such as PyTorch or TensorFlow.

Funding: no specific stipend is listed in the post, but the professor notes that graduate scholarships may be available from provincial, federal, and private-sector sources, including NSERC and provincial funding. Domestic students are especially encouraged to plan early for scholarship deadlines, and international students may also have opportunities.

Application window: the post mentions a Fall 2026 deadline for domestic students of June 1. The lab page also advises applying early for scholarship consideration. Interested candidates should apply through the University of Guelph graduate application process, name Iuliia Kotseruba as a potential supervisor, and submit the Google Form linked in the post.