Biostability challenges in drinking water distribution networks: Effect of temperature and water sources.
The production of safe drinking water requires continuous attention due to increased demands and quality issues. Climate effects, including rising temperatures, influence water quality during distribution, and in urban areas, the close proximity of different cables and pipes may further impact water quality. Additionally, increased demand and prolonged periods of drought in summer force drinking water companies to access new water sources and mix water from different sources. This may result in changes in water quality, particularly in the microbial composition and its activity. This can lead to a decrease in water quality and complaints about taste and odour.
Biostability is referred to as a stable microbial population that doesn’t grow during transport. However, changing temperatures and mixing will alter the microbial population. The question is whether those changes are reducing water quality or create unstable, growing, populations. Insights into the presence and activity of the microbial population can be obtained through Next Generation Sequencing and complemented by a chemical profile obtained by Non-Target Screening. The Bioinformatic and Cheminformatic databases can subsequently be coupled with Machine Learning approaches to correlate and interpret the effects of the conditions described above. From there on, a predictive model for water quality in highly demanding urban areas can be built.
Your assignment
You will investigate the effect of differences in water temperature and source mixing on the microbial and chemical quality of the water. Additionally, you will use this data to build a comprehensive model to predict these effects on the biological stability of the drinking water during distribution. The project will combine laboratory experiments to simulate different conditions with molecular (Next Generation Sequencing) and analytical techniques (Non-target Screening) to monitor dynamics. Real-life data and samples from distribution systems will be provided by the drinking water companies.
Your work will help ensure safe drinking water, now and in the future. Minimizing interventions and allowing drinking water companies to better address future challenges posed by climate change and increasing water demands.
Your profile
You hold an MSc degree in molecular biology, microbiology, systems biology, bioinformatics, or a related discipline. You have a strong interest in machine learning, mathematical modelling, data science, and experimental research. Experience with molecular biology techniques, microbiome analysis, or data modelling is considered an advantage. You are motivated to work at the interface of fundamental and applied science.
Keywords: drinking water microbiology, biostability, Next Generation Sequencing, Non-Target Screening, bioinformatics, cheminformatics, Machine learning
The team
University promotor: Prof. dr. G.J.W. Euverink (University of Groningen, Faculty of Science and Engineering, Products and Processes for Biotechnology)
University co-promotor: prof. dr. Bayu Jayawardhana (University of Groningen, Faculty of Science and Engineering, Mechatronics and Control of Nonlinear Systems)
Wetsus co-promotor and daily supervisor: Dr. Inez Dinkla
Project company partners: Monitoring & Quality theme. Brabant Water, Vitens, WON, Waterkracht, DEEPbv, Murata, Omrin, aqa.earth, Easy measure.
Only applications that are complete, in English, and submitted via the application webpage before the deadline will be considered eligible.
Guidelines for applicants: https://phdpositionswetsus.eu/guide-for-applicants/
