Postdoc in Computer Vision for Analysis of Cattle Behaviour and Welfare

Postdoc in Computer Vision for Analysis of Cattle Behaviour and Welfare

SLU - Swedish University of Agricultural Sciences

Uppsala, Sweden

Swedish University of Agricultural Sciences (SLU) is seeking a postdoctoral researcher with strong methodological expertise in AI and computer vision for research focusing on animal welfare and behavior in dairy cattle.

About the position

This postdoctoral position offers the opportunity to work with data-driven research at the intersection of AI, computer vision, animal welfare, and behavior. The position is aimed at a method-oriented researcher interested in developing and applying computer vision–based methods in real-world settings.

The project is part of the European Partnership on Animal Health and Welfare (EUPHAW) and focuses on the development of methods to quantify and analyze behavior and welfare in dairy cattle using large-scale video and sensor data collected in barn environments.

The research is conducted at SLU in close collaboration with European research groups within EUPHAW. The work takes place in a multidisciplinary research environment, where methodological development in AI and computer vision is combined with applications in animal welfare and Precision Livestock Farming. The position offers scope for independent research, methodological development, and international collaboration.

Within the scope of the position, the researcher is expected to:

• conduct independent and high-quality research within the scope of the position;
• publish research results in international, peer-reviewed scientific journals;
• communicate research and research findings to both academic and non-academic audiences;
• participate in national and international collaborations, including travel.

Background

We are looking for a candidate who:

• has a clear methodological profile in AI and computer vision, regardless of disciplinary background;
• has worked independently with the development, training, and validation of computer vision models;
• is comfortable working in multidisciplinary research environments, where methods are applied to biological or real-world problems.

Qualifications

The applicant must:

• hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline);
• have documented experience in computer vision, where the PhD project was fully or substantially method-focused on computer vision and/or AI-based image or video analysis;
• have very strong knowledge of machine learning, with practical experience in model development and evaluation;
• have good programming skills in at least one relevant language;
• have a strong ability to communicate orally and in writing in English.

Desirable qualifications

• experience in computer vision for video analysis (e.g. tracking, pose estimation, behavior recognition);
• experience working with large-scale or long-term video data;
• experience with model evaluation and generalization in noisy, real-world data;
• experience combining video and sensor data;
• applied experience with AI in biological or veterinary systems.