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Improving pig health through advanced predictive techniques

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  • Full or part time
    Dr C Gomes
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

SRUC and the University of Stirling are seeking a student to participate in a doctoral research project to explore the use of machine learning for improving the health and productivity of farm animals. This interdisciplinary project brings together the expertise of University of Stirling in computing and data science, and SRUC expertise in epidemiology and knowledge of the pig industry to enable a student to combine novel, modern quantitative analyses with biological expertise to achieve improved health outcomes. This project has the potential to offer considerable economic impact for Scottish animal agriculture.

The pig sector in Scotland has been at the forefront of the development of proactive, innovative health improvements. A considerable range of data sources have been collated via the Scottish Pig Health Network (SPHN) to drive further improvements in pig health. These include information related to endemic and zoonotic diseases, animal production, animal movements and farm demographics, antimicrobial usage and data regarding animal welfare. In collaboration with University of Stirling we propose to explore the application of modern data science and machine learning techniques to questions in animal population health via a jointly funded PhD studentship, utilising the SPHN data collection. This will bring added value to the SPHN project.

Applicants should meet the following criteria:
•A bachelor’s or master’s degree in computing science, data science, mathematics, or a closely related field, or a track record of research or work history in such a field in combination with a post-secondary degree in another relevant subject is required.
•The ability to work with an interdisciplinary team of computing and data scientists, informaticians, population health scientists, and veterinarians is critical.
•Applicants should have relevant computing abilities and skills, including programming in one or more languages used for machine learning and data science (e.g., Python, R, C/C++).
•Very good written and oral communication skills are required.
•The student should have an interest in animal agriculture and husbandry.
•The student must be willing to spend time in Stirling and Inverness to interact with all members of the project team.

The student’s time will be split between Stirling and Inverness. It is anticipated that approximately the first half of the project duration will be spent in Stirling in proximity to the University of Stirling, while roughly the second half will be spent embedded in the SRUC Epidemiology Research Unit in Inverness.

Funding Notes

The stipend will be set at UKRI recommended levels for a 3.5 year-period and the studentship is funded to pay domestic tuition fee levels for UK/EU students. The student will receive an annual student stipend of £15,099 for the first academic year. The expected start date is 1 October 2019. This studentship is funded to pay the tuition fees of UK/EU nationals only. Non UK/EU nationals must provide evidence of sufficient funds to cover the higher international student tuition fee level (approximately £16,740 per year would be required).

How good is research at SRUC - Scotland’s Rural College in Agriculture, Veterinary and Food Science?
(joint submission with University of Edinburgh)

FTE Category A staff submitted: 57.37

Research output data provided by the Research Excellence Framework (REF)

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