Self‑Funded PhD: Acoustic Monitoring and Artificial Intelligence for Precision Assessment of Dairy Cattle Welfare
Animal Health, Behaviour & Welfare
Location: Newport, Shropshire TF10 8NB
PostType: Full Time
ContractType: Fixed Term - 3 years full-time or equivalent part-time
ClosingDate: 23.59 hours BST on Tuesday 30 June 2026
Reference: PHD-GC-01
Acoustic Monitoring and Artificial Intelligence for Precision Assessment of Dairy Cattle Welfare
Precision livestock farming is transforming how animal health and welfare are monitored on farms. However, many current monitoring systems rely primarily on visual or activity‑based sensors, meaning important behavioural and physiological signals may be missed. Sound within livestock environments contains a wealth of information about animal behaviour, health and emotional state, yet it remains relatively under‑utilised in commercial dairy systems.
The successful candidate will undertake a structured training programme at the start of the PhD to develop skills in programming, data analysis, machine learning and signal processing. They will also gain experience in animal behaviour and welfare research, precision livestock technologies, and interdisciplinary collaboration between animal science and data science.
Responsibilities
During the PhD, the research will involve:
* Collecting and analysing sound data from dairy housing environments.
* Linking acoustic patterns to behavioural and health indicators.
* Developing computational models capable of detecting meaningful welfare‑related signals.
* Exploring integration of acoustic information with other farm data to improve the reliability of automated welfare assessment.
* Working closely with the co‑supervisors at Harper Adams University and Nottingham Trent University.
Qualifications
Applicants must hold, or expect to hold, a Master’s degree (MSc) in a relevant discipline such as:
* Veterinary Medicine
* Veterinary Sciences
* Animal Behaviour and Welfare
Strong quantitative skills are desirable. Prior experience in one or more of the following would be advantageous:
* Behavioural observation and welfare assessment
* Bioacoustics or signal analysis
* Programming in Python or R
* Statistical modelling
Applicants without prior AI experience are encouraged to apply, as structured AI/ML training will be provided.
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