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.
Breast Cancer in young women is becoming more common and is associated with particularly adverse outcomes. The project seeks to better understand the mechanisms of tumour development in such patients, some of whom have a known family (genetic) history of disease and for others there is no known genetic reason for this to occur. We will be studying a series of samples from patients diagnosed at this young age, involving the morphological annotation of clinical specimens followed by: Aim 1 - the characterisation of DNA mutations as they accumulate through different stages of neoplastic development; and Aim 2 - the concomitant RNA transcriptional programs as they change through these stages of development. The latter data will be generated through recently developed technology known as spatial transcriptional profiling. The project will generate significant volumes of data, which will need sophisticated analysis using some conventional and some increasingly complex bioinformatics and machine learning approaches. The proposed student will work at this analytical stage of the project, in developing new tools to analyse the complex data. The student will therefore contribute to the generation of analytical pipelines for this new technology, which is increasingly becoming a method of choice in many disciplines. Further outcomes would relate to the development of a mechanistic understanding of the very early stages of tumour development in young patients, and this will have future significance in the areas of disease screening and treatment.
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
Associate Professor Peter Simpson
Faculty of Medicine
Email: p.simpson@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 cancer biology, genomics, spatial transcriptomics, and bioinformatics/machine learning would be of benefit to someone working on this project.
The applicant will demonstrate academic achievement in the field(s) of bioinformatics and the potential for scholastic success.
A background or knowledge of breast cancer, genomics, transcriptomics, and spatial profiling 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.