Mapping Global Health Through Wastewater: A PhD in Biological Pathogen Surveillance and Environmental Genomics

About the Project

Wastewater-based epidemiology (WBE) is a rapidly emerging and highly interdisciplinary research field that uses chemical and biological markers in wastewater to provide near-real-time, population-level insights into health, behaviour, and environmental exposures. By capturing information from entire communities in an anonymous and non-invasive way, WBE overcomes key limitations of traditional public-health surveillance, including reporting delays, sampling bias, and dependence on clinical testing. Its power as an early-warning and decision-support tool, most visibly demonstrated during the COVID-19 pandemic, has transformed how we monitor public health: enabling faster outbreak detection, improved trend analysis, and more equitable, data-driven interventions at scale. That transformation is still accelerating and this studentship sits at its leading edge.

Are you ready to help map the health of humanity? This PhD studentship offers a rare chance to do exactly that. The project will contribute to Wastewater Watch, a pioneering global initiative aiming to capture the first simultaneous snapshot of human health worldwide through wastewater analysis (https://wastewaterwatch.org/). This initiative spans over 40 locations, with coordinated sampling campaigns designed to generate a truly global baseline of human health. You will join an international, high-impact programme at the forefront of environmental and public-health research, contributing to work that has real-world consequences for how governments and health agencies respond to emerging threats.

The successful candidate will have access to state-of-the-art analytical infrastructure within the National Wastewater-Based Public Health Laboratory in Wales (twinned with Verily Life Sciences), including long- and short-read genomic sequencing, high-throughput qPCR (HT-qPCR), high-throughput laser direct infrared microplastics analysis (HT-LDIR), and a dedicated cloud-based supercomputing platform, supported by experienced laboratory and computational personnel. These cutting-edge tools will be deployed across a rich and diverse target landscape, from pathogenic viruses and bacteria to fungal threats, antimicrobial resistance genes, and environmental indicator organisms, using both untargeted metagenomic discovery and targeted molecular quantification. Together, these approaches will generate a multi-pathogen, multi-kingdom portrait of human and environmental health that has never before been achieved at global scale.

The studentship is jointly supervised across two world-leading research groups, at Bangor University and the University of Bath, giving you access to complementary expertise, facilities, and networks spanning environmental genomics, mass spectrometry, and translational public-health science. Working closely with a fellow PhD student based at the University of Bath, and embedded within a collaborative, multidisciplinary national research laboratory, you will contribute to generating a unique, global-scale dataset. This work will deliver unprecedented insights into human health at the population level, positioning you at the forefront of modern public-health and environmental science, while equipping you with highly sought-after skills in advanced analytical methods, international collaboration, and translational research.

Upon graduation, you will be exceptionally well-placed for careers in academic research, public-health agencies, environmental consultancy, or the biotechnology and diagnostics industries.

We are looking for a motivated and curious graduate with a strong background in a relevant discipline such as environmental microbiology, public health, medical science or a related field. Experience in molecular laboratory or computational techniques is desirable but not essential, enthusiasm, rigour, and a collaborative spirit matter most.

To find out more or to apply, please contact Prof. Davey Jones (d.jones@bangor.ac.uk).