Remote monitoring solutions for beef cattle welfare and productivity

Summary

The focus of this PhD will be to develop and evaluate innovative methods to capture, analyse and optimise data derived from a range of technologies and sensors to optimise beef cattle health, welfare and efficiency in feedlot. Data sources may include a combination of animal, climate, farm and processing plant data and others. This multidisciplinary project interrelates diverse areas of research including livestock science, behaviour analysis, complex data acquisition and analysis, machine learning and optimisation using sophisticated modelling tools. The broad scope of the project, and its interdisciplinary nature, allows emphasis in specific area/s to be placed according to candidate's background and expertise.

A complimentary scholarship for this project is available. To find out more, refer to the Postgraduate Research Stipend and Supplementary Scholarship in Digital Agriculture Data61.

The supervisory team for this project also includes Dr Reza Arablouei (CSIRO), Dr Brano Kusy (CSIRO) and Dr Dave Henry (CSIRO).

Supervisor(s)

Associate Professor Cameron Edward Fisher Clark, Professor Sergio (Yani) Garcia

Research Location

School of Life and Environmental Sciences

Program Type

PHD

Synopsis

There is a clear need for advanced integration and utilisation of sensor-derived data to optimise monitoring, intervention and feeding management of individual beef cattle in feedlot. Technologies exist that allow animal behaviour and traits to be monitoring in real-time but these have not been integrated with other sources of information from the animal, the weather and the whole system.
This PhD will be to develop and evaluate innovative methods to capture, analyse and optimise data derived from a range of technologies and sensors to optimise individual cow sorting at induction, health monitoring and pen feeding in feedlot. 
A range of methodologies including controlled and feedlot studies, machine learning and advanced modelling is envisaged to be used. Due to its interdisciplinary nature, this PhD opportunity would suit a broad range of candidates with contrasting background and expertise. The scope of the project, as well as the specific areas of expertise of the supervisory team,  are broad, allowing  emphasis within the project to be placed on different area/s

Additional Information

This PhD opportunity will be based at Camden campus or a combination of sites including CSIRO facilities in Brisbane and The University of Sydney in Camden or Sydney as part of the School of Life and Environmental Sciences and the Sydney Institute of Agriculture.

The candidate must have a valid driver license and be willing to travel to University and commercial farms and CSIRO facilities. All students and staff working at the University's farms are required to be vaccinated against Q fever.

A complimentary scholarship for this project is available. To find out more, refer to the Postgraduate Research Stipend and Supplementary Scholarship in Digital Agriculture Data61.

The supervisory team for this project also includes Dr Reza Arablouei (CSIRO) and Dr Brano Kusy (CSIRO).


In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include: 

  • Confidential disclosure and registration of a disability that may hinder your performance in your degree; 
  • Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.); 
  • Ability to perform independently and/or with minimal supervision; 
  • Ability to undertake certain physical tasks (e.g. heavy lifting); 
  • Ability to undertake observatory, sensory and communication tasks; 
  • Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden); 
  • Ability to work in confined spaces or at heights; 
  • Ability to operate heavy machinery (e.g. farming equipment); 
  • Hold or acquire an Australian driver’s licence; Hold a current scuba diving license; 
  • Hold a current Working with Children Check; 
  • Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.) 
You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

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Keywords

digital, agriculture, Data61, CSIRO, Life and Environmental

Opportunity ID

The opportunity ID for this research opportunity is: 2367

Other opportunities with Associate Professor Cameron Edward Fisher Clark

Other opportunities with Professor Sergio (Yani) Garcia