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EPSRC PhD Studentship in: Risk-based investment decision tools that account for uncertainty in modelling studies that protect the ecology of surface water bodies

Posted: 03.03.2020

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Project Description

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

EPSRC PhD Studentship in: Risk-based investment decision tools that account for uncertainty in modelling studies that protect the ecology of surface water bodies

Start Date: 28 September 2020 (contract duration 4 years)
Closing Date for Applications: 20th April 2020

Integrated catchment water quality models consisting of linked river and urban drainage models contain considerable predictive uncertainty. However, what are the implications of this uncertainty when implementing the solutions to achieve compliance with environmental regulations?

Recent research has shown that analysing uncertainty could lead to more robust and lower cost solutions. Little is known about how knowledge of uncertainty would influence any decision maker, and personal risk preferences are believed to be important. There is a need for UK case studies illustrating strategies for decision making under uncertainty.

The project involves modelling and design of a baseline solution for a water quality study, and researching uncertainty in the predictions. Tools to enable uncertainty analysis would be developed with Stantec, a major international consultancy in the water sector. Decision makers in water companies would subsequently be interviewed to investigate how they react to different levels of the risk of failure. A framework would be built to incorporate model uncertainty into an objective investment decision making strategy for solutions to protect natural surface waters.

The research programme to be completed in this project will be undertaken in 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. Students will benefit from a bespoke research and skills training scheme delivered by world leading experts from academia and industry, access to world leading experimental and computational facilities as well as regular close contact with industry and end user partners. CDT WIRe is committed to promoting a diverse and inclusive community, and offers a range of family friendly, inclusive employment policies. For further information visit the web site at: https://cdtwire.com/

The project will be supervised by Dr Alma Schellart and Prof Simon Tait in collaboration with experienced staff from Stantec.

The selection criteria for the position are;
• Have a good honours degree (or equivalent experience) in Engineering, Physical Science, Mathematics, Environmental Sciences 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.
• Aptitude for research as evidenced by previous experience.
• Ability to develop and apply mathematical and statistical concepts of uncertainty to water quality modelling tools.
• Ability to code in a high level computational language.
• Enthusiasm for research concerning surface water quality.
• Willingness to keep up to date with ongoing research.
• Willingness to author and contribute to reports and publications based on research outputs.

How to apply
Interested candidates should email a covering letter and their Curriculum Vitae to Lindsay Hopcroft ().
For information and informal enquiries please contact: Alma Schellart ()

Funding Notes

Eligibility Criteria
Normal EPSRC funding eligibility applies to this award, so students must have a relevant connection with the UK (usually established by residence).

Stipend: This post will fully cover university tuition and provide a tax-free stipend for UK students of £19,000 per year.

 

Further details can be found here 

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