Leveraging near-infrared spectroscopy (NIRS) technique combined with artificial intelligence (AI) in detecting AMR organisms in water

Culture based methods and molecular techniques such as polymerase chain reaction and metagenomics are used for AMR monitoring in water environments. However, culture-based methods are time consuming and molecular techniques are costly and require prior knowledge for target genes whereas metagenomics are costly and require integration of other omics data for functional insights.
The aim of this PhD project is to test the ability of Infrared light technique for rapid detection of the most common bacteria related to AMR i.e. multidrug-resistant (MDR) Enterobacterales. We will focus on extended-spectrum beta-lactamases and Carbapenemase-producing Enterobacterales in E coli, Klebsiella and Enterobacter. We will identify unique biomarkers associated with these bacteria, develop a standard scanning protocol for field testing and test on a preliminary scale the protocol in the real-world settings to detect AMR organisms in water. 
Project outcomes: We will determine unique NIR biomarkers for several bacteria associated with AMR in water samples, develop AI algorithms for them.

You will have access to state-of-the-art tools and technologies for infrared analysis within the school of the Environment and molecular analysis of bacteria samples at UQCCR.
You will also have the opportunity to work nationally and internationally with leading experts in Australia and around the world.

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 molecular biology, sequencing, clinical bacteria, machine learning would be of benefit to someone working on this project.

You will demonstrate academic achievement in the fields of clinical bacteria and molecular techniques including sequencing and data analysis and the potential for scholastic success.

A background or knowledge of clinical bacteria, molecular technologies including qPCR and genome sequencing, manuscript writing is highly desirable.

You must submit an expression of interest (EOI) by 20 February, 2026 25 December, 2030.

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 Maggy Lord (maggy.lord@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: SPECTROSCOPY-LORD
4. Link to Scholarship Advertisement: https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/leveraging-near-infrared-spectroscopy-nirs-technique-combined-artificial-intelligence-ai-detecting-amr-organisms-water

Submit an EOI