Project summary
- Program
- PhD
- Location
- St Lucia
- Research area
- Biological sciences, Biomedical and clinical sciences, Health sciences, Information and computing sciences, Mathematical sciences
Project description
Single-cell sequencing technologies, such as scRNA-seq and scATAC-seq, have transformed our ability to interrogate molecular biology at cellular resolution, providing unprecedented opportunities to understand the aetiology of complex diseases.
Integrating single-cell omics with human genetics enables us to move beyond association towards causality, identifying which genes influence disease risk, in which cell types, and through what regulatory mechanisms. Meanwhile, genome-wide association studies (GWAS) continue to generate vast amounts of data on the genetic architecture of common diseases.
A key challenge is how to effectively integrate cellular omics with population-scale genetic data to inform disease prevention, diagnosis, and treatment.
You will develop and apply cutting-edge statistical methods and open-source software tools to advance our understanding of the genetic mechanisms underlying common diseases and to improve individual disease risk prediction.
You will develop Bayesian methods to address one or more of the following challenges:
- prioritising the most relevant biological contexts for disease
- identifying causal genes and regulatory pathways
- improving disease risk prediction and characterising subtype heterogeneity.
Scholarship
This is an Fellowship support scheme scholarship project that aligns with a recently awarded Australian Government grant.
The scholarship includes:
- living stipend of $37,500 per annum tax free (2026 rate), indexed annually
- your tuition fees covered.
Learn more about the Fellowship support scheme scholarship.
Supervisor
Principal 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 statistical genomics, high-dimensional data analysis, and scientific programming would be of benefit to someone working on this project.
You will demonstrate academic achievement in the fields of statistical genetics, biostatistics, computational biology, or a related quantitative discipline, and the potential for scholastic success.
A background or knowledge of Bayesian modelling or machine learning, genome-wide association studies (GWAS), single-cell omics analysis, and programming in R, Python, or C++ is highly desirable.
How to apply
This project requires candidates to commence no later than Research Quarter 1, 2027. You can start in an earlier research quarter.
You must submit an expression of interest (EOI) by the closing date for the research quarter (RQ) you want to start in:
Before you apply
- Check your eligibility for the Doctor of Philosophy (PhD).
- Prepare your documentation.
- If you have any questions about whether the project is suitable for your research interests, contact Dr Jian Zeng (j.zeng@uq.edu.au).
When you apply
To apply, submit an expression of interest (EOI) for the program. You don't need to apply separately for the project or scholarship. How to submit an EOI
In your EOI, complete the 'Scholarship/Sponsorship' section with the following details:
- Are you applying for an advertised project: 'Yes'
- Project: 'Fellowship project scholarship'
- Scholarship Code Listed in the Advertisement: DISEASE-ZENG
- Link to Scholarship Advertisement: https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/integrating-single-cell-genomics-complex-disease-genetics