EPSRC PhD Studentship in: Big Data, Network Complexity and Machine Learning to Deliver Targeted Pro-active DWDS Maintenance

Details

The University of Sheffield, Sheffield Water Centre in collaboration with South West Water and the Centre for Doctoral Training in Water Infrastructure and Resilience.

EPSRC PhD Studentship in: Big Data, Network Complexity and Machine Learning to Deliver Targeted Pro-active DWDS Maintenance

Stipend: This post will fully cover university tuition and provide a tax-free stipend for

Home and Overseas students of £24,000 per year.

Closing Date for Applications: 30th June 2024

Start Date: 30th September 2024 (contract duration 4 years)

This fully funded project provides an unrivalled opportunity to apply machine learning techniques to address engineering challenges impacting the operation of drinking water distribution systems. The research will integrate water quality data with aspects including hydraulics and GIS records from an operational network leading to the development and field testing of innovative and targeted management strategies to ensure the supply of safe drinking water to over 1.8 million people. Techniques such as complex network theory and self-organising maps will be used to train predictive models to inform pro-active network maintenance with the outcomes being reviewed and annually updated. This project offers a unique chance to develop data-driven solutions that can deliver significant real-world impact on public health and well-being.

Drinking water is treated at water treatment works and we must ensure its continued high standard as it is transported through distribution networks to consumers. There is an urgent need to understand treatment to tap interactions through these massive and aging systems such that we can best manage drinking water supply. Targeting where, and when, maintenance strategies are required, and identifying the optimal approach, are critical to deliver a pro-active risk based approach. This internationally significant research will collect evidence to justify and test network management strategies, such as flushing and flow conditioning, that will ultimately secure resilience in this essential infrastructure and support the ability to face future challenges such as population shifts and climate change.

The research programme to be completed in this project will be undertaken as part of the EPSRC Centre for Doctoral Training in Water Infrastructure and Resilience (CDT WIRe). CDT WIRe is a collaboration between the three leading UK Universities in water resilient infrastructure. You would be part of an active and friendly community. Students will benefit from a bespoke training scheme delivered by world leading experts from academia and industry, access to world leading experimental and computational facilities as well as close and regular contact with industry and end user partners. Resources are available for international collaboration and conference attendance. CDT WIRe is committed to promoting a diverse and inclusive community, and offer a range of family friendly, inclusive employment policies. For further information on the CDT WIRe scheme visit the web site at: https://cdtwire.com/

The project will be supervised by Dr Stewart Husband, Dr Killian Gleeson and Prof. Joby Boxall in collaboration with partners from with South West Water. The normal place of work is expected to be at the University of Sheffield, with close regular interaction with South West Water and extended periods at study sites, with travel and subsistence costs provided for these periods. There will be generous opportunities to travel to visit our academic and industry partners in both the UK and overseas.

Eligibility Criteria

This studentship is subject to standard RCUK eligibility criteria. It is open to all

students with Home or Overseas residency (subject to a maximum quota of

overseas students per training grant).

The selection criteria for the position are;

• Enthusiasm for research and the topic area

• A good honours degree (or equivalent experience) in Engineering, Physical Science, Mathematics, Computer Sciences, Physical Geography or a related subject.

• Good level of written and oral communication skills, as appropriate for disseminating research and communicating with project partners.

• Willingness to collaborate with other researchers, industry and end-users.

• An interest in using data science to solve engineering problems.

• Some experience in a coding language such as Python.

How to apply

Interested candidates should email a covering letter and their Curriculum Vitae to Miss Lindsay Hopcroft ([email protected]).

For information and informal enquiries please contact: Dr Stewart Husband ([email protected])