Real-time, three-dimensional, and super-resolution electromagnetic medical imaging

This project aims to develop a prototype electromagnetic (EM) imaging system that demonstrates the potential to advance the underlying physical mechanisms and elevate the imaging quality of electromagnetic imaging to the next level. We will seek a solution to a prominent research question: Can real-time imaging with super-resolution performance be achieved by reformulating the fundamental physical principles of EM imaging?

You will develop a physics-guided, deep learning-based imaging algorithm to generate super-resolution images in real-time. An imaging platform will then be designed and constructed to experimentally validate the developed algorithm in several applications, including medical imaging, infrastructure inspection, and body imaging for surveillance. 

You will be located in UQ's School of Electrical Engineering and Computer Science, with a world-class intellectual research environment in the discipline of electromagnetic imaging and microwave engineering research.

You will work in a dynamic research group dedicated to applied electromagnetics and engineering artificial intelligence, with applications in physics-guided deep learning applied in electromagnetic medical imaging, sensing, and microwave circuit design. You will benefit from access to state-of-the-art facilities, including multi-port vector network analysers, dielectric probe kits for dielectric characterisation, and a fully automated scanning system. You will also have access to UQ's High Computing resources, such as Bunya clusters, equipped with powerful GPUs such as NVIDIA's H100. 

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 applied electromagnetics and machine learning would be of benefit to someone working on this project.

You will demonstrate academic achievement in the fields of applied electromagnetics, machine learning in physics and the potential for scholastic success.

A background or knowledge of computational electromagnetcis, microwave engineering, and deep learning in electromagnetics is highly desirable.

You must submit an expression of interest (EOI) by 23 March, 2026 23 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 Dr Lei Guo (l.guo3@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: ELECTROMAGNETIC-ABBOSH
4. Link to Scholarship Advertisement: https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/real-time-three-dimensional-and-super-resolution-electromagnetic-medical-imaging

Submit an EOI