Characterising blood oxygenation changes in functional human brain imaging

In this funded PhD project, you will focus on quantifying blood oxygenation changes to improve functional human brain imaging (fMRI). While fMRI is a widely used technique, unspecific "vascular" signals from downstream blood oxygenation changes currently degrade the spatial specificity of the measurements. You will address this limitation through three distinct aims: measuring vessel-specific changes in blood oxygenation using 3D Echo-Planar Imaging; characterising the topology and topography of human venous angioarchitecture using machine learning segmentation; and implementing a forward model to simulate and remove macrovascular signal contributions from fMRI data.
 
This research aims to ultimately increase the spatial specificity of fMRI to the level of individual cortical laminae and columns. You should have an interest in neurovascular coupling, high-resolution imaging, or computational modeling.
 
This funded scholarship includes a stipend (living allowance) and tuition fees.

Working under the primary supervision of Professor Markus Barth at The University of Queensland, you will benefit from close international collaboration with PI Poser, a specialist in high-resolution venous imaging, and PI Polimeni, a pioneer in vascular modelling of fMRI signals. The project involves utilising advanced 3D Echo-Planar Imaging sequences to acquire fast, high-resolution images during various active conditions, including visual stimulation, hand movements, and breathing challenges.
 
The project work will include adapting quantitative susceptibility mapping pipelines to derive oxygenation levels and employing self-supervised learning techniques to segment complex venous structures. You will work with computational pipelines using subject-specific angioarchitecture as input, a significant departure from previous single-voxel approaches.

This project is supported by the Research project scholarship.

Learn more about the Research project scholarship.

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 MRI physics, medical image analysis, machine learning, or computational neuroscience would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field(s) of physics, biomedical engineering, or neuroscience and the potential for scholastic success.

A background or knowledge of MRI Image processing: quantitative susceptibility mapping or segmentation strategies; machine learning: self-supervised learning techniques or classical segmentation approaches; and/or
computational modelling is highly desirable.

You must submit an expression of interest (EOI) by 30 June, 2026 31 March, 2026.

Before you apply

1. Check your eligibility for the Doctor of Philosophy (PhD).
2. Prepare your documentation.
3. If you have any questions about whether the project is suitable for your research interests, contact Professor Markus Barth (m.barth@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:

1. Are you applying for an advertised project: 'Yes'
2. Project: 'Research project scholarship'
3. Scholarship Code Listed in the Advertisement: OXYGENATION-BARTH
4. Link to Scholarship Advertisement: https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/characterising-blood-oxygenation-changes-functional-human-brain-imaging

Submit an EOI