Improving cattle health by developing novel data fusion and machine learning approaches to Internet of things livestock data

Applications are invited to join the University of Nottingham BBSRC iCASE Studentship to undertake an innovative four-year PhD training programme.

Project description

An effective, automated precision monitoring solution would be of huge benefit for the early detection of disease in cattle, however, there are no algorithms for cattle health yet that have high predictive value for early disease detection.

We have teamed up with Industry partners Prognostix Ltd and British telecommunications and by using ‘big data’ gathered from multiple sensors on cow health, production and activity this PhD aims to explore following key questions:
1. What methods are best for data fusion (signal level fusion, feature level fusion or decision level fusion for predicting cattle health (disease events: (respiratory disease/diarrhoea/lameness/high somatic cell counts) and production (milk, weight gain) and what are penalties of those (with respect to performance and implementation?
2. What features are important and have higher predictive value for early prediction of disease? How early can we predict a disease event on cattle farm using this metadata?

The successful applicant will use various machine learning algorithms, such as Neural Networks, Support Vector Machines and Random Forests and other ensemble methods.

This project will be based in the School of Veterinary Medicine and Science and will be supervised by team of academics from areas of veterinary epidemiology, agri-informatics, bioinformatics, machine learning and signal processing.

Supervisory team will be Dr. Jasmeet Kaler (University of Nottingham), Dr Tania Dottorini (University of Nottingham) and Prof Saeid Sanei (Nottingham Trent). Student will spend 3 months with Industrial partner Prognostix Ltd.

See our research in similar areas: https://www.kaler-researchgroup.co.uk/

Applications are invited from motivated students who have/expect to graduate with a first/upper-second UK honours degree, or equivalent qualifications gained outside the UK in Biology, Veterinary, Animal Science, Computer Science or Informatics, Mathematics or engineering. Students with an appropriate Masters degree and programming ability are particularly encouraged to apply.

How to apply
Applicants should go to https://www.nottingham.ac.uk/bbdtp/icase-studentships/icase-studentships.aspx to download the specific application and reference forms. Applications should include: a fully completed application form; a CV of no more than two A4 pages; a transcript of module marks achieved at the time of submission; and two references. Application forms and CVs should be named in the following format: SURNAME-initial-DTP_BBSRC_iCASE-application.doc (.docx or .pdf) and SURNAME-initial-BBSRC_iCASE-cv.doc (.docx or.pdf) e.g. SMITH-A-BBSRC_iCASE-application.doc

Applications should be sent via email with the subject line ‘BBSRC iCASE Studentship’ to ([Email Address Removed]) by the deadline: noon, 10th July 2018.

References should be sent directly from the referees to ([Email Address Removed]) by the deadline: noon, 10th July 2018. Please note it is the applicant’s responsibility to ensure that the references are sent in good time for the deadline. Further details are on the reference form.

Enquiries should be sent to: [Email Address Removed]

Please quote ref: BBSRC iCASE

Closing date: 10th July 2018