Post-doctoral Research Associate (PDRA) (Fixed-term)
- University of Nottingham
- United Kingdom, LND
- Jul 9, 2026
Job Description:
A post-doctoral position is available to take a leading research role in an industry-facing HBLB funded research project entitled “Toward Racehorse Injury Prevention: A Computer Vision-Based Approach for Monitoring Behaviour in Stabled Racehorses and Early Identification of Musculoskeletal Injuries”, a project to be conducted in collaboration with Vet Vision AI and Johnston Racing.
The project uses computer vision and artificial intelligence to identify behavioural indicators of musculoskeletal injury — primarily limb injuries — in stabled racehorses. Continuous monitoring of behaviour in the stabled environment offers a unique opportunity to capture rich behavioural data to validate a computer vision tool measuring 24-hour time budgets and behavioural patterns, with the goal of developing alerts that flag injury risk during the training season. Vet Vision AI has developed this technology to characterise behaviour in healthy horses and to detect patterns associated with disease in hospitalised horses. This project applies these techniques to racehorse injury monitoring and prevention for the first time.
Identifying behavioural patterns that precede injury would be a step-change for equine health, welfare and performance. It would open a new area of research into racehorse behaviour and underpin early-warning systems with the potential to change how the industry monitors and protects horses in training.
This is a senior postdoctoral role that demands deep expertise in equine behaviour and veterinary science, strong industry credibility, and the judgement to lead delivery across academic and commercial partners. The successful applicant will join a collaborative and well-connected research group within the School of Veterinary Medicine and Science (SVMS). The post is primarily research-focused, with some teaching and administrative duties. The role involves significant time working directly with racehorses through the project partner Johnston Racing, and close collaboration with industry partner Vet Vision AI.
The postholder will collaborate widely across SVMS research teams and contribute to mentoring undergraduate and postgraduate researchers. SVMS was ranked second in the UK for research power in the most recent Research Excellence Framework and has consistently ranked first in the National Student Survey since 2011. The post is based at Sutton Bonington Campus and will involve independent travel to project partners Vet Vision AI (Derbyshire) and Johnston Racing (North Yorkshire). This is a three-year, full-time (36.25 weekly hours) post offered at an enhanced salary reflecting the seniority of the role.
Further information is available in the role profile. To apply for this vacancy please click ‘Apply Now’ to complete your details.
Please contact Laura Randall ([email protected]) if you have further questions about this role. Please note that applications sent directly to this email address will not be accepted.
Closing Date: 05 Aug 2026
Category: Research and Teaching (R&T)
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Job Description:
A post-doctoral position is available to take a leading research role in an industry-facing HBLB funded research project entitled “Toward Racehorse Injury Prevention: A Computer Vision-Based Approach for Monitoring Behaviour in Stabled Racehorses and Early Identification of Musculoskeletal Injuries”, a project to be conducted in collaboration with Vet Vision AI and Johnston Racing.
The project uses computer vision and artificial intelligence to identify behavioural indicators of musculoskeletal injury — primarily limb injuries — in stabled racehorses. Continuous monitoring of behaviour in the stabled environment offers a unique opportunity to capture rich behavioural data to validate a computer vision tool measuring 24-hour time budgets and behavioural patterns, with the goal of developing alerts that flag injury risk during the training season. Vet Vision AI has developed this technology to characterise behaviour in healthy horses and to detect patterns associated with disease in hospitalised horses. This project applies these techniques to racehorse injury monitoring and prevention for the first time.
Identifying behavioural patterns that precede injury would be a step-change for equine health, welfare and performance. It would open a new area of research into racehorse behaviour and underpin early-warning systems with the potential to change how the industry monitors and protects horses in training.
This is a senior postdoctoral role that demands deep expertise in equine behaviour and veterinary science, strong industry credibility, and the judgement to lead delivery across academic and commercial partners. The successful applicant will join a collaborative and well-connected research group within the School of Veterinary Medicine and Science (SVMS). The post is primarily research-focused, with some teaching and administrative duties. The role involves significant time working directly with racehorses through the project partner Johnston Racing, and close collaboration with industry partner Vet Vision AI.
The postholder will collaborate widely across SVMS research teams and contribute to mentoring undergraduate and postgraduate researchers. SVMS was ranked second in the UK for research power in the most recent Research Excellence Framework and has consistently ranked first in the National Student Survey since 2011. The post is based at Sutton Bonington Campus and will involve independent travel to project partners Vet Vision AI (Derbyshire) and Johnston Racing (North Yorkshire). This is a three-year, full-time (36.25 weekly hours) post offered at an enhanced salary reflecting the seniority of the role.
Further information is available in the role profile. To apply for this vacancy please click ‘Apply Now’ to complete your details.
Please contact Laura Randall ([email protected]) if you have further questions about this role. Please note that applications sent directly to this email address will not be accepted.
Closing Date: 05 Aug 2026
Category: Research and Teaching (R&T)
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