Advancing AI tools for hazard detection in potable water sources

The provision of critical and safe drinking water to Australian communities requires ongoing and accurate monitoring of water supplies for effective decision-making. Current monitoring relies on several analytical methods and large data sets to investigate subsets of potentially hazardous contaminants. New hazard monitoring tools are urgently required to detect a comprehensive range of contaminants such as pesticides or disinfection by-products and respond to contamination events from spills or algal bloom incidents. 
This project aims to advance scientific and mathematical discovery by developing a new framework for combining advances in High-Resolution Mass Spectrometry contaminants detection and analysis with computational Machine Learning algorithms that will allow for rapid, accurate, and robust identification of chemical threats in drinking water systems, enabling the processing of large and complex datasets.

The project aims to support water authorities, and environmental and health protection regulators nationally and internationally to meet growing water demands. The innovation aims to further contribute to global research and water security, offering a versatile solution that can be expanded for other types of environmental and human monitoring. The candidate will engage with scientists, mathematicians, government and industry partners in an exciting multi-disciplinary project.

QAEHS is internationally recognized for research excellence in the environmental sciences. The centre has established state-of-the-art sampling, analysis and archiving facilities located at the Dutton Park Campus. QAEHS maintains 7x LC-MS/MS and 5x GC-MS instruments, with a dedicated trace analytical laboratory and state-of-the-art instrumentation. The student will join a cohort of >30 HDR students researching human and environmental exposure to environmental contaminants.

The student will be given access to a centre-level travel support award scheme supporting participation at international conferences. The student will receive full access to their own computer and workstation. The research is supported through a number of grants and collaborations including a generous research consumable budget.

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 environmental science, analytical chemistry, computer science, and mathematics would be of benefit to someone working on this project.

A background or knowledge of analytical chemistry or machine learning tools is highly desirable.

Before you apply

Before submitting an application you should:

1. check your eligibility for a Doctor of Philosophy (PhD)
2. prepare your documentation
3. contact Dr Sarit Kaserzon (k.sarit@uq.edu.au) to discuss your interest and suitability
4. submit your application by 5 May, 2025 5 May, 2025.

When you apply

You apply for this scholarship when you submit an application for your program. 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'
• ‘Other’, then ‘Research Project Scholarship’ and in the ‘Name of scholarship’ field enter POTABLE-KASERZON.

Apply now