Computational modelling approach to understanding shoot architecture including plant branching and flowering

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.

Shoot architecture is an important agricultural trait underpinning plant growth and yield, and it has long been studied from the perspective of plant hormones. Our laboratory has developed a detailed model description of the mechanisms of shoot branching involving genetic and physiological networks, plant hormones, sugars and nutrients. The student will convert that description to a computational model that captures dynamic processes on phenotype and phenology including the timing, location, genetics and physiological state of the plant. It will involve iterative collaborative experimentation, both in vivo and in silico, during implementation of the model in a dynamic functional structural plant modelling (FSPM) platform such as L-systems. This plant modelling project would build upon a wealth of data on gene expression, hormone levels and quantitative data on the initiation and subsequent growth of branches from dormant axillary buds in garden pea and Arabidopsis. A core innovation will be the integration of large-scale network modelling into the FSPM framework.

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)


Professor Christine Beveridge

School of Biological Sciences


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 mathematical and computational principles for modelling would be of benefit to someone working on this project.

A background or knowledge of IT, mathematics, physics or engineering is highly desirable. Experience in programming in C++, R, Python or equivalent would be helpful, as well as knowledge of L-systems or graph theory. Previous experience working with plants in the laboratory could be useful, although it is not required.

Latest commencement date

If you are the successful candidate, you must commence by Research Quarter 1, 2023. 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