Healthy and sustainable livestock through fine-grained behavioural monitoring using new hybrid AI on wearables and video University of Bristol in United Kingdom

Background:Do you want to help revolutionise how we understand animal behaviour and welfare? Social network data is now a powerful tool for studying both human and animal behaviour, and this studentship offers the chance to contribute to cutting-edge research in this field. At the University of Bristol, we have built the John Oldacre Centre, where advanced technology like 50+ video cameras and artificial intelligence (AI) are used to monitor and track cows in a dairy farm setting [1]. This has allowed us to study subtle changes in social behaviour, which could help us predict diseases and improve animal welfare.Aims and objectives:Monitoring cows in open fields presents a new challenge - video footage is not practical when they roam outdoors. Based on our experience predicting declining health with animal-worn accelerometers [2], we have now developed our own bespoke and fully programmable wearable sensor and are excited to use it for new research. In this exciting studentship, you will help develop a novel system that learns to combine video monitoring with wearable sensors (such as collar and leg devices) to better track cow behaviour in both indoor and outdoor settings.Methods:You will spearhead the creation of hybrid system that will use AI to automatically link video data with wearable sensors through deep learning AI-based transformer models, improving our ability to understand animal behaviour wherever they are. Concepts you will work on particularly include transfer learning of behavioral classifiers from video to accelerometry data. You will also explore how indoor and outdoor environments affect animal behaviour and how to translate the system into practice, including how to optimise camera and sensor placement to gather the best data. Key references:[1] https://doi.org/10.1016/j.compag.2021.106133[2] https://www.biorxiv.org/content/10.1101/2020.08.03.234203v4Supervisors:This project is a collaboration between data science, machine vision, and animal science and behavioural biology experts at the University of Bristol (Prof Andrew Dowsey, Dr Neill Campbell, Dr Daniel Enriquez-Hidalgo and Dr Suzanne Held) and Rothamsted Research’s North Wyke Farm Platform (Dr Jordana Rivero-Viera; Prof Paul Harris), a large-scale grazing research platform investigating the future of sustainable livestock farming.  Whether you have a background in computing or the mathematical sciences and are interested in machine vision and deep learning, or come from biosciences and want to develop new skills in AI, this studentship offers a tailored training package to support your development. Join us in exploring how cutting-edge technology can transform our understanding of animal behaviour and welfare! How to apply: Please visit the Bristol Veterinary School website Funded 4-year PhD Scholarship | Bristol Veterinary School | University of Bristol for details of how to apply and the information you must include in your application - please read the Detailed Application Guidance section from the website for more information about this. If your application is shortlisted, you will be invited to interview on or before 17th January. Interviews will take place on Microsoft Teams on 29th January. Start date Sept 2025.Candidate requirements: Standard University of Bristol eligibility rules apply. Please visit PhD Veterinary Sciences | Study at Bristol | University of Bristol for more information.Contacts: please contact [email protected] with any queries about your application. Please contact the project supervisor for project-related queries: [email protected]