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Harnessing 3D cameras and deep learning for on-the-fly automated body condition and mobility analysis to improve cattle welfare


Bristol Veterinary School

Monday, December 07, 2020 Competition Funded PhD Project (UK Students Only)

About the Project

The project:

A growing world population and climate change are stressing food availability. High animal welfare and health practices are more important than ever to satisfy societal demands for the livestock sector. In this PhD project, 3D video technology with the latest Intel cameras will be used to unobtrusively provide stress-free monitoring of incremental changes in individual cow mobility and body condition. The aim is to understand behavioural cues preceding observed lameness to improve cow health, welfare and productivity and hence increase the climate and environmental sustainability of milk production. This will realise a system that can be transplanted into farms without extensive instrumentation, allowing farmers and others in the value chain such as vets, nutritionists and livestock advisers to make use of much more precise, consistent and frequent measurements, creating greater opportunities to improve cow performance and welfare.

The studentship would suit either a mathematical or computational student interested in sustainable food production, or someone with veterinary or 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 animal welfare assessment, and use this and cutting edge AI to build and apply the system across the studentship timeline so we can develop a better understanding of lameness. The student will be based 50%/50% at two leading, geographically close institutes – Bristol Robotics Laboratory at the University of West of England, and Bristol Veterinary School & Visual Information Laboratory at the University of Bristol, and will benefit from a broad cross-disciplinary supervision team, led by Prof Melvyn Smith (Machine Vision) and Prof Andrew Dowsey (One Health Data Science), who have published state-of-the-art work in this area that will be built upon (see https://doi.org/10.1016/j.compind.2018.02.011 , https://arxiv.org/abs/2006.09205 , https://www.biorxiv.org/content/10.1101/2020.08.03.234203v2) . Data collection and validation will harness the Bristol Veterinary School’s John Oldacre Centre for Sustainability and Welfare in Dairy Production, a new research centre based at our Wyndhurst dairy farm that will include blanket 24/7 video coverage of all our 185 cows linked to data on production, emissions and veterinary assessments (https://www.bristol.ac.uk/vet-school/research/john-oldacre-centre--farm-research-data-platform).

This studentship will start in September 2021.

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.

Standard University of Bristol eligibility rules for PhD admissions also apply. Please visit http://www.bristol.ac.uk/study/postgraduate/2021/health-sciences/phd-veterinary-sciences/ for more information.

Contacts: Prof Andrew Dowsey:


Funding Notes

Funding: For eligible students (see above), funding is available to cover Home tuition fees and UKRI Doctoral Stipend ( £15,009 p.a. for 2019/20, updated each year) for 4 years. An enhanced stipend is available for eligible students with a recognised veterinary degree (£23,164 p.a. for 2019-2020). Research training budget will also be provided to supervisors.

Most international students (including EU students) are ineligible for this funding. However, we will consider competitive self-funded applications from non-UK nationals who are supported by their own government agencies, international organisations or private funders.

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