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Exploiting non-traditional data sources to identify smallholder pig and poultry farmers and their role in disease outbreaks

  • Full or part time
  • Application Deadline
    Sunday, March 03, 2019
  • 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 social media, search data, and other new and developing sources of information to better characterise the population of small holder farms in the UK. This interdisciplinary project brings together expertise of the University of Stirling in computer science and SRUC expertise in epidemiology, smallholder behaviour and animal disease to enable the student to combine quantitative analysis with biological expertise to achieve improved surveillance for animal disease and enhance the health and welfare of farm animals on small holdings.

The amount of data available on livestock ownership varies between sectors. Commercial pig and poultry farmers are registered and well monitored. Small scale farmers, on the other hand, are much more difficult to keep track of. The aim of this proposal is to apply automated data science approaches to social media and search data to identify smallholder farmers, whom we know communicate through Facebook groups, Twitter and other fora. We will also test the use of Internet-based surveillance systems to monitoring infectious diseases (using Google trends, natural language processing of Twitter feeds and computer vision analysis of social media images, for example). Surveillance systems built on Internet data are economically, logistically and epidemiologically appealing and have shown significant promise. They can also run continuously, providing a live source of information regarding current animal health issues among small holders.

Applicants should have a bachelor’s or master’s degree in computing science, data science, mathematics, or a closely related field, or a track record of research as well as programming in one or more languages used for machine learning and data science (e.g., Python, R, C/C++).

The student will be located at Stirling and the SRUC Epidemiology Research Unit in Inverness and registered with the University of Stirling in the Division of Computing Science and Mathematics and starting on 1st October 2019.

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 £14,777 (£15,009 in 2019/20).This studentship will fund to pay the tuition fees at home fees rate only. International students 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)

Click here to see the results for all UK universities

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