PaquetLab — Computer Vision for Animal Production

Computer vision and artificial intelligence are already transforming healthcare, transportation, and manufacturing. Agri-food today offers an exceptional application ground, where technological innovation meets major societal challenges: animal welfare, food safety, and the sustainability of animal production.

At PaquetLab (Université Laval), we develop computer vision and deep learning algorithms to monitor animal health and behavior directly in the field — in dairy sheep farming (Ovision project) and in pork production (Research Chair in Digital Vision Applied to the Pork Sector, in partnership with MAPAQ, Les Éleveurs de porcs du Québec, Olymel and CDPQ). These projects give access to real-world data rarely available in academic research — video and images captured on farms, in clinics, and in processing plants — for both scientific and concrete impact on animal production.

PhD in Applied Computer Vision

$30,000 CAD / yr·multiple applications considered·candidates from across Canada and abroad welcome

The project

This doctoral project aims to design and validate robust computer vision algorithms to detect health issues early, track animal behavior, and automate body-condition assessment from video and images captured under real conditions. The student will tackle cutting-edge problems: object detection and multi-animal tracking in complex environments, behavioral analysis, 3D reconstruction,



image processing under uncontrolled conditions, and the development of robust models that transfer to the field.

Profile sought

Master's degree in computer science, computer or software engineering, applied mathematics, artificial intelligence, or a related field. Strong skills in deep learning (PyTorch/TensorFlow) and experience in computer vision (detection, segmentation, tracking, 3D). Autonomy, creativity, and a strong interest in real-world applications of AI in agriculture.

Depending on the candidate's country of origin, we anticipate that the appointment could begin in January/May 2027.

Master's in Applied Computer Vision

The project

This Master's project is an excellent entry point into applied AI research. The student will contribute to a concrete project — data collection, development of data‑capture tools, and training and validation of computer vision models — within a supervised team that works directly with partners from the animal industry.

Profile sought

Bachelor's degree in computer science, computer engineering, electrical engineering, food/agricultural engineering, or an equivalent field. Solid interest — ideally some prior experience — in computer vision and deep learning. Resourceful, motivated candidates eager to contribute to concrete solutions for agriculture.

Depending on the candidate's country of origin, we anticipate that the appointment could begin in January/May 2027.

📌 PhD and Master's Positions in Applied Computer Vision · Université Laval (Quebec City)
🏢 Université Laval
📍 Quebec City