Developing AI-based MRI methods for microscopic imaging

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.

We are currently recruiting two PhD students to innovate on novel MRI methods that can be eventually applied to neuroscience and neurological diseases. Our lab is focusing on these research topics:

  1. MR image processing through advanced optimization techniques and deep learning

To develop advanced image reconstruction methods for MRI post-processing techniques, such as Quantitative Susceptibility Mapping (QSM) and accelerated MRI acquisition reconstruction. Particularly through (1) image optimization/regularization, compressed sensing, and (2) deep learning and artificial intelligence.

  1. Fast, multi-parametric, and quantitative MRI acquisition methods at ultra-high field

To significantly reduce the total scan time for each subject, by (1) accelerating individual scans with parallel imaging techniques at ultra-high field, and (2) designing novel MRI sequences that produce multi-contrast weighted images and multi-parametric quantitative maps from a single MR acquisition.

  1. Brain imaging applications in neuroscience and neurological diseases

To apply comprehensive image analysis on different MRI methods to better understand neuroscience, such as brain development in children and structural and functional connectivity of the brain, as well as some of the neurological diseases such as Alzheimer’s disease/Dementia, Parkinson’s disease, Multiple Sclerosis, Schizophrenia, and Stroke.

Scholarship value

As a scholarship recipient, you'll receive: 

  • living stipend of $28,854 per annum tax free (2022 rate), indexed annually
  • tuition fees covered
  • single Overseas Student Health Cover (OSHC)

Supervisor

Dr Hongfu Sun

School of Information Technology and Electrical Engineering

Email: hongfu.sun@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 MATLAB/python programming, deep learning platforms, linux environment and MR physics would be of benefit to someone working on this project.

The applicant will demonstrate academic achievement in the field(s) of neuroimaging and artificial intelligence and the potential for scholastic success.

A background or knowledge of computer or software engineering and biomedical engineering is highly desirable.

Latest commencement date

If you are the successful candidate, you must commence by Research Quarter 1, 2022. 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