PhD opportunity in SE Water

Application deadline: until filled

We offer this PhD opportunity with a generous top-up scholarship at OPTIMA Monash University, Clayton node. Our PhDs are 3.5 years that include a minimum of one-year industry placement, ensuring that our graduates are industry-ready upon conclusion.
We invite potential PhD candidates to submit an expression of interest, see link below. Before applying, please familiarise yourself with Monash University’s admission requirements, as a PhD cannot be offered if you do not meet the universities’ stringent requirements, Monash University (https://www.monash.edu/graduate-research/future-students/apply), Monash University will only process applications for OPTIMA students after you have completed this EOI, attended an industry interview and have been provided with an OPTIMA letter of acceptance.
Project details:
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, including a tuition scholarship (for international students). 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.
Required knowledge and skills: 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.
OPTIMA CIs: Assoc. Professor Guido Tack
Associate Investigator: Dr Mario Boley
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