PhD Scholarship - Automated phenotyping and precision livestock technologies
Two scholarships are available to investigate methods to improve cattle access to paddock-based automated monitoring tools and integrating data gained into genetic evaluation tools. The PhD projects are designed to advance the use of precision livestock technologies by improving the performance of walk-over-weigh and automated livestock monitoring technologies in extensive cattle production systems, and the application of the data gained to advance producer and industry performance.
Scholarship Value: $30,000 per year
Length of Scholarship: 3 years
Number Available: 2
Opening Date: 12 October 2020
Closing Date: 30 November 2020
|Study Level||Postgraduate (Research)|
|Year of Study||Future; First year|
|Study Region||Rockhampton Queensland|
|Study Mode||All modes|
|Study Load||Full time|
To be eligible for the Scholarship, an applicant must:
- have prior study to a masters or equivalent level in a livestock and technology related field; and
- be currently onshore in Australia ready to commence the project as soon as possible
Applications are invited from candidates who have or can demonstrate:
- Prior study to a masters or equivalent level in a livestock and technology related field
- Skills in digital technologies including developing hardware and software
- Ability to work independently in the field
- Ability to meet deadlines
- Teamwork skills
- An interest in working with industry or external stakeholders.
Candidates with equivalent or complementary experience are also encouraged to apply.
Students will work within CQUniversity’s internationally renowned Precision Livestock Management team. The MLA project funding the scholarships already has detailed performance recording systems that provide students with access to cattle performance measures derived from automated livestock measuring systems (ALMS). The project team will provide technical support and guidance to ensure a successful PhD program.
Applications must include all necessary supporting documents. Incomplete applications will not be considered. Applicants will need to supply the following supporting documentation:
- Written submission
- Academic Transcripts
Enquiries and applications should be submitted by email to Professor Dave Swain at email@example.com.
The application should include:
- A cover letter describing how your skills and research expertise address the selection criteria;
- Your current resume and academic transcripts together with a list of publications and projects;
- Names of two referees, together with email and phone contact information; and
- If applicable, examples of scientific writing (e.g. published scientific articles, research reports, thesis).