The project:
Social network data now gives us unprecedented means to research human and animal behaviour, and recently has found much value in the early prediction of mental health disorders and degenerative disease. Human behaviour in the general environment is extremely complex, so there is much potential in investigating more structured animal environments where we have found evidence that social activity subtly changes even under mild (subclinical) infection (https://doi.org/10.3168/jds.2020-20047).
This PhD project is aimed at developing vision‐based artificial intelligence (AI) techniques to build dynamic social networks to understand changes in social dynamics associated with early and chronic subclinical disease in cows. Through a long‐term study of our complete 185‐head herd at our John Oldacre Centre for Sustainability and Welfare in Dairy Production, network constructs hold information on key aspects of high welfare, sustainable animal production, and could eventually be translated back to monitor structured environments in the human domain.
This studentship will combine and extend our AI methods and the underlying behavioural science to develop a system that identifies and tracks the movements of individuals, and then detects and classifies social interactions and their initiator. It builds on previous work in our labs, where we have developed new AI methodology that can individually identify and track Holstein‐Friesian cows with high accuracy (https://arxiv.org/abs/2006.09205),as well as demonstrating that facial recognition in livestock is achievable (https://doi.org/10.1016/j.compind.2018.02.016), thus potentially unlocking the ability to automatically detect grooming or aggressive nature of their social interactions.
The studentship would suit either computational student interested in social networks and behaviour, or someone with biosciences expertise who wishes to build up artificial intelligence skills – in either case a tailored training package will be developed to suit. The student will learn the key facets of health‐relevant behaviour assessment and use this and cutting edge AI and social network analysis to build and apply the system across the studentship timeline. The student will be based 50%/50% at two leading, geographically close institutes – Bristol Robotics Laboratory at the University of West of England with Dr Mark Hansen and Professor Melvyn Smith, and Bristol Veterinary School at the University of Bristol, with data scientist Professor Andrew Dowsey, animal biometrics experts Dr Laszlo Talas and Dr John Fennell, and behavioural scientists Dr Suzanne Held and Prof Mike Mendl.
Please note: This project in collaboration with the University of Bristol and the University of the West of England (UWE) is subject to a joint degree award. Successful applicants will be registered at both these institutions, and graduates will be awarded a joint degree from these two institutions upon successful completion of the PhD programme.
This studentship will start in September 2023.
Contacts: [Email Address Removed]
Supervisory team:
Lead supervisors: Prof Andrew Dowsey (University of Bristol), Dr Mark Hansen (University of the West of England)
Dr Suzanne Held (University of Bristol), Prof Melvyn Smith (University of the West of England), Dr Laszlo Talas (University of Bristol), Dr John Fennell (University of Bristol), Prof Mike Mendl (University of Bristol)
Collaborators: Dr Tilo Burghardt (University of Bristol)
Host institution: University of Bristol, University of the West of England (UWE). Submit applications for this project to University of Bristol
How to apply:
This studentship is part of the BBSRC SWBio Doctoral Training Partnership (https://www.swbio.ac.uk/). Please apply from https://www.swbio.ac.uk/programme/projects-available/.
Candidate requirements:
Please see https://www.swbio.ac.uk/programme/eligibility/ for conditions specific to this funding.
Due to complexities and restrictions associated with visas for part-time studies, we are currently unable to accept part-time international students to the programme Project adjustments, part-time study and flexible working – SWBiosciences Doctoral Training Partnership
Standard University of Bristol eligibility rules for PhD admissions also apply. Please visit http://www.bristol.ac.uk/study/postgraduate/2023/health-sciences/phd-veterinary-sciences/ for more information.
Our aim as the SWBio DTP is to support students from a range of backgrounds and circumstances. Where needed, we will work with you to take into consideration reasonable project adaptations (for example to support caring responsibilities, disabilities, other significant personal circumstances) as well as flexible working and part-time study requests, to enable greater access to a PhD. All our supervisors support us with this aim, so please feel comfortable in discussing further with the listed PhD project supervisor to see what is feasible.
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