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HDR Scholarship: Physics-Informed and Explainable AI for Water Security: Uncertainty-Aware Modelling from Multisource Environmental Observations

This project integrates diverse environmental observations including in‑situ water‑quality measurements, flow data, hyperspectral reflectance, and satellite imagery from platforms such as Sentinel and Landsat, accessed through CSIRO’s EASI environment. These rich datasets come from real‑world CSIRO Aqua-Watch pilots and Hunter Water Corporation, with the Williams River catchment and Grahamstown Dam serving as primary testbeds. 

Primary location of student

University of Southern Queensland,37 Sinnathamby Boulevard, Springfield Central QLD 4300, Australia

Industry engagement component location

CogninetAustralia Pty. Ltd, Level 5, 29-35 Bellevue St, Surry Hills NSW 2010, Australia

Other locations

CSIRO Black Mountain,CluniesRoss Street, Acton ACT 2601, Australia

Ideal student skillset

A strong interest in environmental modelling, artificial intelligence, and real‑world impact.

A background in one or more of the following: machine learning, data science, environmental engineering, hydrology, physics‑based modelling, statistics, or remote sensing.

Experience with Python, scientific computing, or geospatial data tools (e.g., GIS, satellite imagery processing) will help you hit the ground running, but curiosity and willingness to learn are just as important.

Students who enjoy working with complex datasets, developing new algorithms, or exploring how physical principles can guide AI models will thrive in this project.

An interest in explainable AI, uncertainty quantification, or environmental monitoring is a bonus.

You will collaborate with researchers from CSIRO and university partners, gaining hands‑on experience with cutting‑edge environmental datasets and modelling platforms. This project suits students who want to build advanced technical skills while contributing to Australia’s long‑term water security.

Value

Total living expense stipend of AUD $324,233

The scholarship provides an annual stipend comprising the CSIRO Industry PhD scholarship and an industry-funded top-up. The annual rates supplied for this opportunity are:

  • 2027: AUD $49,513
  • 2028: AUD $50,998
  • 2029: AUD $52,528
  • 2030: AUD $54,104

The maximum scholarship tenure is four years, subject to the scholarship conditions and satisfactory progress. Any applicable periods of prior study towards the degree will be deducted from the available tenure.

Additional Project Expense and Development funding supports research operating costs and research skills development. This funding is separate from the student’s personal stipend. The annual rates are:

  • 2027: AUD $13,390
  • 2028: AUD $13,792
  • 2029: AUD $14,205
  • 2030: AUD $14,632

The program also provides joint university, CSIRO and industry supervision, structured professional development, and an industry engagement component of at least 60 full-time days.

 

To be eligible applicants must:

  • Be an Australian or New Zealand citizen, or an Australian permanent resident.
  • Meet UniSQ’s PhD admission and English language requirements, to meet one of the following:
    • have completed an Australian-university Bachelor honours degree with First Class Honours or Second Class Honours (Division A) or equivalent (with a thesis comprising at least two units), or,
  • have completed an Australian university master’s degree (with a thesis comprising at least two units) or equivalent, or
    • other qualifications and/or equivalent experience as determined by the project team to be equivalent research experience suitable for admission into PhD, and,
  • Have not previously completed a PhD.
  • Not be receiving another primary scholarship.
  • Be able to commence the program in the year of the offer.
  • Enrol as a full-time PhD student, expected to spend at least 38 hours per week.
  • Be based at the agreed project location or locations and comply with any applicable UniSQ external enrolment requirements.
  • Be eligible to commence or continue a PhD in January 2027

Applicants should demonstrate academic achievement, experience relevant to the research, and motivation to undertake an industry-focused PhD. Programming, quantitative analysis, machine learning or environmental modelling experience will be considered favourably. See details below.

To be eligible applicants must:   

  • A strong interest in environmental modelling, artificial intelligence, and real‑world impact.
  • A background in one or more of the following: machine learning, data science, environmental engineering, hydrology, physics‑based modelling, statistics, or remote sensing.
  • Experience with, or ability to acquire Python, scientific computing, or geospatial data tools (e.g., GIS, satellite imagery processing) will help you hit the ground running, but curiosity and willingness to learn are just as important.
  • Be a student who enjoy working with complex datasets, developing new algorithms, or exploring how physical principles can guide AI models will thrive in this project.
  • Have an interest in explainable AI, uncertainty quantification, or environmental monitoring is a bonus.
  • Be eager to develop independence and collaborate with researchers from CSIRO and university partners, gaining hands‑on experience with cutting‑edge environmental datasets and modelling platforms. This project suits students who want to build advanced technical skills while contributing to Australia’s long‑term water security.

To apply, please ensure you have digital copies of the below information:

Application must be made via the UniSQ Scholarship Application Management System by the closing date.

If you require assistance in completing your application please download the  Scholarships Online Application Manual (PDF 2.14MB).   

20 November 2026  

Further information about this scholarship can be obtained from Professor Ravinesh Deo by emailing ravinesh.deo@unisq.edu.au