Computer Vision Applied to Animal Production
Description
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.
This 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.
Target start date: January or May 2027 (PhD), January 2027 (Master's)
Research Field
-2D/3D computer vision: object detection, segmentation, tracking, and 3D reconstruction
-Deep learning and applied artificial intelligence
-Video-based animal health and welfare monitoring
-Behavioral analysis and animal posture recognition
-Image processing under real, uncontrolled field conditions (farms, clinics, processing plants)
-Development of data-capture tools (cameras, sensors, field instrumentation)
-Precision livestock farming and smart animal production
-Applications in dairy sheep and pork production
Research Supervisor
Éric Paquet
Research Environment
PaquetLab, Université Laval, Québec, Canada
The PaquetLab is a multidisciplinary research environment where artificial intelligence, computer vision, and animal science come together. Our team brings together students and researchers from varied backgrounds — computer science, engineering, animal science, agri-food — united by a shared goal: developing concrete computer vision solutions that meet the real needs of farmers and producers.
Our projects are built on real-world data, captured directly on farms, in clinics, and in processing plants — whether for the health and welfare of dairy sheep (Ovision project) or for pork production and processing (Research Chair in Digital Vision). This close connection to the field and to our industry partners ensures strong scientific impact, as well as real, measurable impact for the animal production industry.
The lab is affiliated with Université Laval's IID (Institut intelligence et données) and CRDM (Big Data Research Center), giving our students access to a broad network of researchers in artificial intelligence and data science, as well as state-of-the-art computing resources to train and deploy large-scale models.
Web Site
Financial Aid Available by Program of Study
Doctorate in Computer Science
Program descriptionFinancial Aid Available*
Financial Aid Related to Research Project
$30000 per year for 4 years.
Program-Specific Financial Aid
Graduate Studies Awards
| Milestone |
Amount |
Progression scholarship 1 - 7
|
7 x $1,600 |
| Progression scholarship 8 |
$800 |
| Total |
$12,000 |
Université Laval: Student Financial Aid
Supplemental Tuition Fee Exemption Scholarship Program: Entitles international students to pay Canadian student tuition fees, for overall savings of around $45,000.
* Amounts shown represent maximum financial aid available. Certain conditions apply. Subject to change without prior notice. For further information, contact sponsoring organizations directly. Doctorate in Electrical Engineering
Program descriptionFinancial Aid Available*
Financial Aid Related to Research Project
$30000 per year for 4 years.
Program-Specific Financial Aid
Graduate Studies Awards
| Milestone |
Amount |
Progression scholarship 1 - 7
|
7 x $1,600 |
| Progression scholarship 8 |
$800 |
| Total |
$12,000 |
Université Laval: Student Financial Aid
Supplemental Tuition Fee Exemption Scholarship Program: Entitles international students to pay Canadian student tuition fees, for overall savings of around $45,000.
* Amounts shown represent maximum financial aid available. Certain conditions apply. Subject to change without prior notice. For further information, contact sponsoring organizations directly. Master's Degree in Computer Science with thesis
Program descriptionFinancial Aid Available*
Financial Aid Related to Research Project
$24000 per year for 2 years.
Program-Specific Financial Aid
Graduate Studies Awards
Université Laval: Student Financial Aid
* Amounts shown represent maximum financial aid available. Certain conditions apply. Subject to change without prior notice. For further information, contact sponsoring organizations directly. Master's Degree in Electrical Engineering with thesis
Program descriptionFinancial Aid Available*
Financial Aid Related to Research Project
$24000 per year for 2 years.
Program-Specific Financial Aid
Graduate Studies Awards
Université Laval: Student Financial Aid
* Amounts shown represent maximum financial aid available. Certain conditions apply. Subject to change without prior notice. For further information, contact sponsoring organizations directly.
Desired Profile
- Agronomy
- Computer Software
- Electrical Engineering
- Computer Engineering
- Software Engineering
- Bioinformatics
- Artificial intelligence
Requirements and Conditions
- Required degree: Master's in computer science, computer or software engineering, applied mathematics, artificial intelligence, or a related field (for the PhD); Bachelor's in computer science, computer engineering, electrical engineering, food/agricultural engineering, or an equivalent field (for the Master's)
- Strong skills in deep learning (PyTorch, TensorFlow)
- Experience in computer vision (object detection, segmentation, tracking, 3D reconstruction)
- Programming skills (Python)
- Autonomy, creativity, and a strong interest in real-world applications of AI in agriculture
- Motivated, resourceful candidates with a genuine desire to help animal production
The projects require solid technical skills: programming (Python), deep learning (PyTorch, TensorFlow), and hands-on experience in computer vision (object detection, segmentation, tracking, image processing). A background in applied mathematics, statistics, or signal processing is also an asset.
Beyond technical skills, we are above all looking for motivated, resourceful students who can work independently on real-world data under sometimes unpredictable field conditions (farms, clinics, processing plants), and who are genuinely driven to put technology to work for the health and welfare of animal production.
Required Documentation
- Cover letter
- Curriculum vitæ
- Student transcript
Highly motivated applicants should send a cover letter, a CV, and academic transcripts (BSc and MSc for PhD applicants) by email to eric.paquet@fsaa.ulaval.ca, specifying the position and project of interest. Applications are accepted until the end of September.
Important: Master's positions are reserved exclusively for students from Québec. PhD positions, on the other hand, are open to candidates from across Canada and internationally.
Application Deadline
October 2, 2026
Find Out More
Éric Paquet
Professeur
Faculté des sciences de l'agriculture et de l'alimentation
eric.paquet@fsaa.ulaval.ca