GIS and remote sensing for improved weed management in direct seeded rice

Project opportunity

This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.

Rice crop intensification and yield improvements have ensured self-sufficiency in Cambodia and Laos. However, labour limitations have dramatically reduced traditional rice planting methods and led to a rise in direct-seeded rice (DSR) methods. One of the main challenges for DSR farmers is the significant reduction in yield caused by weeds. The project focuses on developing an integrated weed management package for two lowland agroecosystems ensuring sustainable rice production and improved grain quality in DSR. Under this project, we will use state-of-the-art GIS and remote sensing applications for land use and weed management, such as drones and satellite images for land mapping, weed identification and improved herbicide application.

We are seeking a highly motivated and enthusiastic PhD researcher to join our project. The candidate will focus on GIS and remote sensing application for land use and weed management, with the aim of increasing rice crop yields and improving quality in DSR systems in Laos and Cambodia.

Scholarship value

As a scholarship recipient, you'll receive: 

  • living stipend of $32,192 per annum tax free (2023 rate), indexed annually
  • tuition fees covered
  • single Overseas Student Health Cover (OSHC)

Supervisor

Dr Jaquie Mitchell

School of Agriculture and Food Sciences

Email: jaquie.mitchell@uq.edu.au

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 processing GIS-related data and relevant software and programming languages (must be proficient in Python or R), and experience in data analysis and interpretation would be of benefit to someone working on this project.

The applicant will demonstrate academic achievement in the field(s) of remote sensing and the potential for scholastic success.

A background or knowledge of agriculture is highly desirable.

Latest commencement date

If you are the successful candidate, you must commence by Research Quarter 1, 2024. You should apply at least 3 months prior to the research quarter commencement date.

If you are an international applicant, you may need to apply much earlier for visa requirements.

How to apply

You apply for this project as part of your PhD program application.

View application process