Trickling filters are one of the most commonly used wastewater treatment technologies in the UK and throughout much of the world. However, the performance of trickling filters can vary enormously from one wastewater treatment facility to another and with respect to time of year and day. If trickling filters systems fail, on-site treatment capacity is reduced and there is an increased risk of permit breaches for ammonia, suspended solids and Biochemical Oxygen Demand (BOD).
In response, this exciting collaborative EngD involving Southern Water and the University of Brighton offers an opportunity to process a unique water-industry-leading dataset spanning over 10 years in order to discover underlying knowledge.
Southern Water is currently the only water and sewerage company (WASC) in the UK to have installed online monitors in its trickling filter treatment systems for many years. These monitors sample the trickling filter’s final effluent for turbidity, ammonia and flow, among other parameters. As a result, the company has more than 10 years of diurnal data for trickling filter operations over a large number of works, which is currently under used and provides a unique optimisation opportunity. By processing the available data, it should be possible for the successful EngD candidate to provide a valuable insight into the operational activity within tricking filters, including trend and pattern identification.
With this information, Southern Water will be able to further develop and improve its on-site operations for trickling filters through optimisation whereby increasing capacity and reducing capital costs for purchasing new filters. The successful candidate will also get to create a risk mitigation model, which can be applied to on-site operations for validation. The model may be subsequently expanded and refined to be used on other sites and potentially shared with the wider wastewater treatment industry.
We are looking for a student with a strong interest and some experience in data analysis and data mining, and statistical methods or AI methods, and a flair for system-level thinking of complex processes. Experience in R or Python is not essential but will be preferred. The successful candidate might also create software for processing and analysing the data. The successful candidate will spend the majority of their time (approximately 75%) at Southern Water’s offices in Falmer, the remaining 25% at the university’s Moulsecoomb campus in Brighton, where taught modules will take place along with academic support and progress monitoring, via the university’s Doctoral College.
The candidate will be based in the School of Computing, Engineering and Mathematics, located within the Division of Mathematical Sciences. The candidate will be able to access relevant masters-level taught modules in Data Management, Programming, Data Visualisation, Business Analytics, Multivariate Statistical Analysis, Stochastic Methods and Forecasting, Data Mining, Risk Analysis and will have access to computer poolrooms, specialist software, including R, SAS, SPSS Statistics and SPSS Modeller.
The Engineering Doctorate is an exciting alternative to the traditional PhD for students who want to work with industry. The four-year programme enables students to experience research at the cutting edge of challenge-driven innovation within the industrial sector whilst at the same time incorporating a training needs orientated, taught component.
Students will spend the majority of their time with the industrial partner in addition to becoming part of the university’s research community. The structured component of the EngD occurs predominantly in the first 12 months of the course but up to one-third may take place as required at later stages to complement the research project. The EngD provides access to a diverse and multidisciplinary range of subjects including those within biomedical and environmental sciences, engineering, business and enterprise, specialist research methods training and communication and outreach activities.