NERC RED-ALERT CDT: Detection of pathogens in rivers with a smart multimodal sensor array module integrated in an autonomous robot platform - PhD via FindAPhD

University of Bath

Bath, UK 🇬🇧

About the Project

This project is one of a number that are in competition for funding from the Red-ALERT CDT for entry in September 2025.

Overview of the Research:

Over 80% of rivers in the UK are affected by multiple sources of diffuse pollution, including sewage and urban pollution, agricultural pollution, and industrial pollution. To minimise risks to the public and the environment, there is a clear need for at-site autonomous multipoint and multimodal sensing and monitoring to pinpoint hazardous discharges in a timely manner and accurately assess the spread and extent of the pollution. In particular, effective spatial-temporal assessments of microbial contamination of waters would minimise the risk of waterborne disease outbreaks.

Nonetheless, currently such sensing and monitoring processes are hindered by the need for multiple sampling and lab-based analysis, which poses severe costs, time consuming, inaccurate measurements and logistic challenges. Our vision is to overcome these challenges with the development of a smart multimodal sensing module for full integration in robot platforms for autonomous and systematic exploration, sensing and detection of key pathogens in water.

This vision will be successfully achieved with a highly multidisciplinary project spanning electrochemistry, microengineering, biotechnology, electronics, robotics and AI fields. The innovative multimodal sensor module will be embedded in a microfluidic chip for at site sample preparation and integrated within an array of probes for water quality monitoring (pH, DO, conductivity, T).

State-of-the-art AI modules will be developed to process and interpret in real-time and accurately the multimodal data outputs from the sensing module. This is a highly interdisciplinary project, including sensing technology, electrochemistry, material science, microengineering, analytical chemistry, AI and modelling. Accordingly, the PhD student will be trained in the relevant disciplines supported by a large supervisory team with relevant expertise in each field.

 Project Keywords: Biosensor, pathogen detection, water quality, AI

Industrial Partners:

Wessex Water are the industrial partner on this project.

Candidate Requirements:

Applicants should hold, or expect to receive, a First Class or good Upper Second-Class UK Honours degree (or the equivalent) with a background in engineering, science and related disciplines. A master’s level qualification would also be advantageous.

 *Non-UK applicants must meet the programme’s English language requirement prior to a formal offer being made.

Equality, Diversity, and Inclusion:

We value a diverse research environment and aim to be an inclusive university, where difference is celebrated and respected. We welcome and encourage applications from under-represented groups.

If you have circumstances that you feel we should be aware of that have affected your educational attainment, then please feel free to tell us about it in your application form. The best way to do this is a short paragraph at the end of your personal statement.

Enquiries and Applications:

Formal applications should be submitted via the Red-ALERT CDT online application form prior to the closing date of this advert.


Funding Notes

Candidates may be considered for a NERC Red-ALERT studentship tenable for 3.5 years. Funding covers tuition fees, a stipend (ÂŁ19,237 p/a in 2024/5) and access to a training support budget.  


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