Project summary
- Program
- PhD
- Location
- St Lucia
- Research area
- Biological sciences
Project description
Aging is a gradual process of functional and homeostatic decline in living systems and the greatest risk factor for most degenerative diseases. At a cellular level, epigenetic changes, including activity change of transcription factors (TF), master regulators of cell identity, play a major role in this functional decline.
The laboratory has performed deep profiling of age-related chromatin accessibility changes with matched gene expression from 22 purified primary mouse cell types across 11 tissues. This allowed us to provide a roadmap of how aging impacts the activity of TFs and the distinct regulatory elements under their control, such as promoters and enhancers (Patrick and Naval-Sanchez et al., Cell Metabolism, 2024).
Recent machine learning and deep learning methods, developed to characterise the regulatory lexicon for DNA-TF interactions, have advanced our understanding of gene regulation. These methods can complement traditional analysis strategies by predicting and annotating the sequence lexicon and the impact of mutations at nucleotide resolution.
Ageing is the number risk factor of disease. Here we hypothesized that an improved understanding of the regulatory logic of enhancers gaining or losing activity during ageing might unlock a better understanding of the mechanisms that predispose to disease.
Therefore, we wish to decipher at base-pair resolution the regulatory lexicon of age-affected gene regulatory elements across cell-types and study their link to healthspan and disease susceptibility.
The project aims to:
- Apply Convolutional Neural Networks (CNNS) and other strategies to decode the grammar of gene regulatory elements with activity changes in ageing.
- Evaluate cross-species conservation of this regulatory grammar (e.g., mouse, dog and human) and our ability to predict age-susceptible gene regulatory elements.
- Assess the impact of genetic mutations in gene regulatory elements with age-altered activity on disease susceptibility using genome-wide association study (GWAS) data.
Research environment
You will join a multidisciplinary team of international researchers dedicated to understanding gene regulatory changes during aging at the bulk and single cell level leveraging diverse epigenome profiling technologies, cutting-edge analysis strategies, and a range of model systems - including mouse/human primary tissues, and cell-based models.
As part of our commitment to excellence in research and professional practice in academic contexts, we are proud to provide our PhD students with access to world-class facilities and equipment, grant writing support, greater research funding opportunities, and other forms of staff support and development.
You will join the benefits of the UQ community and be part of a Group of Eight university. A PhD in Queensland takes up to 4 years. The current position is already funded for three years.
Scholarship
This is an Fellowship support scheme scholarship project that aligns with a recently awarded Australian Government grant.
The scholarship includes:
- living stipend of $36,400 per annum tax free (2025 rate), indexed annually
- your tuition fees covered
- single overseas student health cover (OSHC).
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 genomics/transcriptomic analysis, programming skills in R/python and linux/bash, working in HPC environment, machine learning/convolutional neural network experience, good communication skills and a good command of the English language, both spoken and written would be of benefit to someone working on this project.
You will demonstrate academic achievement in the field/s of genomics and the potential for scholastic success.
A background or knowledge of gene regulation, transcription factors, machine learning, and convolutional neural networks is highly desirable.
How to apply
This project requires candidates to commence no later than Research Quarter 1, 2026. To allow time for your application to be processed, we recommend applying no later than 30 September, 2025 30 June, 2025.
You can start in an earlier research quarter. See application dates.
Before you apply
- Check your eligibility for the Doctor of Philosophy (PhD).
- Prepare your documentation.
- Contact Dr Marina Naval Sanchez (m.navalsanchez@imb.uq.edu.au) to discuss your interest and suitability.
When you apply
You apply for this scholarship when you submit an application for a PhD. 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
- UQ Earmarked Scholarship type.