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Data-Driven Crop Breeding: Enhancing Disease Resistance through Vision-based Digital Phenotyping

Project summary

Program
PhD
Location
St Lucia
Research area
Agricultural, veterinary and food sciences, Biological sciences, Information and computing sciences

Project description

This PhD program, in partnership with NSW DPIRD, aims to advance the use of images to detect and quantify disease in chickpea research and breeding plots. The goal is to replace subjective, qualitative data collection that is inherently error-prone. Cutting-edge computer vision models will enable the collection and analysis of data captured to identify indices/equations that align with traditional/expert scores. Developing a phenotyping platform to screen for disease will provide an efficient and accurate method to rate disease progression. The precision gained from image data will feed into making accurate selections in breeding programs and identifying disease resistance genes.

Research environment

This PhD project is part of the ARC Training Centre in Predictive Breeding, led by UQ. The project will involve placements to NSW DPIRD. All supervisors are CIs and PIs of the ARC Training Centre.

Scholarship

This project is supported by the Research project scholarship.

This scholarship includes:

  • living stipend of $36,400 per annum tax free (2025 rate), indexed annually
  • tuition fees covered.

This scholarship includes:

  • living stipend of $36,400 per annum tax free (2025 rate), indexed annually
  • tuition fees covered.

Learn more about the Research project scholarship.

Supervisor

You must contact the principal supervisor for this project to discuss your interest. You should only complete the online application after you have reached agreement on supervision.

Always make sure you are approaching your potential supervisor in a professional way. We have provided some guidelines for you on how to contact a supervisor.

Preferred educational background

Your application will be assessed on a competitive basis.

We take into account your:

  • previous academic record
  • publication record
  • honours and awards
  • employment history.

A working knowledge of algorithms/computer vision, programming (python), mathematics and statistics would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field of computer science or related areas and the potential for scholastic success.

A background or knowledge of signal/image processing or bioinformatics is highly desirable.

How to apply

Before you apply

Before submitting an application you should:

  1. check your eligibility for a Doctor of Philosophy (PhD)
  2. prepare your documentation
  3. contact Associate Professor Sen Wang (sen.wang@uq.edu.au) to discuss your interest and suitability
  4. submit your application by 4 February, 2025 4 February, 2025.

When you apply

You apply for this scholarship when you submit an application for your program. You don’t need to submit a separate scholarship application.

In your application ensure that under the ‘Scholarships and collaborative study’ section you select:

  • ‘My higher degree is not collaborative’
  • ‘I am applying for, or have been awarded a scholarship or sponsorship'
  • ‘Other’, then ‘Research Project Scholarship’ and in the ‘Name of scholarship’ field enter PHENOTYPING-HUANG.

Apply now