Development of a Risk Prediction Tool for Disease Outbreaks in a Feedlot

Location: East Bendigo, VIC

Duration: 5 months

Proposed start date: July 2019

Please note: Due to funding requirements, students must have Australian or New Zealand Citizenship or Permanent Residency to apply. Any applicants not meeting this requirement will automatically be deemed ineligible for this project.

Project Background

Apiam Animal Health is a company consisting of Australia’s leading production animal and mixed animal veterinary practices. As an industry leader, Apiam is looking to expand its capabilities to help Australian farmers detect and mitigate disease outbreaks which can cause significant flow on effects for the farmers and consumer markets. The goal to develop a risk prediction model is primarily focused on identifying risk factors, assessing efficacy of risk management systems and outlining a mechanism for prevention.

The proposed model will take into consideration meteorological data, historical treatment records, mortality records and herd source.

Research to be Conducted

  • Identification of current and developing methods for risk prediction
  • Understanding of variables and risk factors to be considered in overall feedlot health
  • Prototyping of a risk production model
  • Application and testing of model

Skills Required

We are looking for a PhD student with the following:

ESSENTIAL

  • Strong mathematics/statistics background
  • Simulation and optimisation

DESIRABLE

  • Interest in agricultural economics
  • Experience with databases and programming.
  • Knowledge of SQL
  • Keen problem solver
  • Demonstrated ability leading a project

Expected Outcomes

Developing a model for testing disease outbreak in cattle feedlot.

The research will result in a report that describes the key findings for consideration when managing a feedlot. A summary of these findings will be presented at the final presentation with suggestions to optimise current practices within the industry.

Additional Details

The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.

It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80% of their time on-site with the industry partner.  The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.

The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.

Applications Close

19 June 2019

Reference

APR – 1001