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Smart Water Networks: Optimal placement of monitoring devices

Primary supervisor

Guido Tack


Research area


Water is a resource we usually take for granted. But providing a reliable, safe supply any time you open the tap poses significant logistical challenges. Modern water supply networks use smart meters, embedded sensor devices and complex algorithms to ensure a safe, reliable and affordable product. This project aims to develop novel algorithmic techniques for the optimal deployment of smart sensor networks based on a combination of machine learning and combinatorial optimisation methods.

This is a fully-funded PhD position, with a generous stipend scholarship. You will work closely with our industry partner, South East Water, as well as experts in optimisation and machine learning at Monash University's Department of Data Science and AI and the OPTIMA centre (ARC Industrial Transformation Training Centre in Optimisation Technologies, Integrated Methodologies, and Applications).

Contact me for more details, or complete the Expression of Interest form.

Required knowledge

You should be familiar with basic methods in statistical modelling or machine learning as well as optimisation. Programming skills are important, and the ability to work collaboratively, explore new ideas and communicate well with different stakeholders.

Project funding

Project based scholarship

Learn more about minimum entry requirements.