Master’s and Ph.D. Opportunities in AI for Computer Vision, Autonomous Navigation, and 3D Urban Modeling
York University – Dr. Gunho Sohn’s Laboratory
Master’s and Ph.D. Opportunities in AI for Computer Vision, Autonomous Navigation, and 3D Urban Modeling
Dr. Gunho Sohn’s Laboratory
Dept. Earth and Space Science and Engineering, Lassonde School of Engineering
York University, Toronto, ON M3J 1P3, Canada
Position Description
• Research Areas: Multi-Modal AI, 3D Reconstruction, Visual SLAM, Generative AI, and Urban Modeling
• Positions Available: Master's and Ph.D. Students
• Preferred Start Dates: May 1st, 2025, or September 1st, 2025
• Funding: Competitive stipend (aligned with York University standards), with potential for higher funding based on academic excellence and experience
Dr. Gunho Sohn’s Lab at York University’s Lassonde School of Engineering is offering exciting opportunities for motivated Master's and Ph.D. students to work on advanced AI-driven solutions for computer vision, autonomous navigation, and urban modeling. Students will be part of transformative projects that blend cutting-edge AI techniques with practical applications in 3D mapping, robotics, and smart city development.
Research Themes
• Autonomous Navigation and SLAM: Develop robust Visual SLAM systems using deep learning and multi-modal sensor fusion, integrating LiDAR, cameras, and IMU to achieve scalable, real-time localization and mapping in dynamic environments.
• Generative AI for 3D Urban Modeling: Leverage state-of-the-art techniques such as Neural Radiance Fields (NeRF) and Generative AI to create realistic, context-aware urban scene reconstructions and digital twins.
• AI for Multi-Modal Image Understanding and 3D Reconstruction: Apply Gaussian Splatting, Vision-Language Models (VLMs), and domain-adaptive methods for 3D reconstruction, semantic segmentation, and scene understanding across varied environments.
• AI for Urban Robotics and Simulation: Use reinforcement learning and simulation-based AI to design autonomous robotic systems for urban logistics and disaster response, enabling robust performance in unstructured scenarios.
Required Qualifications
• Bachelor’s or Master’s degree in a relevant field such as Computer Science, Engineering, or related disciplines
• Strong programming skills in Python and/or C++
• Familiarity with widely-used platforms such as PyTorch, JAX, or TensorFlow, and experience working with emerging tools for efficient model training, such as Hugging Face Transformers or Lightning AI.
• Demonstrated research experience in AI, computer vision, robotics, or related areas
• Excellent written and verbal communication skills in English
Research Environment
Dr. Sohn’s lab is located at the Lassonde School of Engineering at York University in Toronto. The lab fosters a collaborative, interdisciplinary research culture and offers access to state-of-the-art facilities. Students will engage with leading academic and industrial partners on high-impact projects aimed at advancing urban AI systems.
To Apply
Interested candidates should submit:
• A brief statement of research interests (max 1 page)
• Curriculum vitae (CV)
• Contact information for two references (letters are not required at this stage)
• Please email your application to [email protected] with the subject line: Master’s/Ph.D. Application – [Your Name].
Application Deadline: January 17th, 2025.
Applications will be reviewed on a rolling basis. Priority will be given to Canadian citizens, permanent residents, or candidates with a valid work permit, but international students with exceptional qualifications are welcome to apply.