Scholarship

Development of origami-paper eDNA sensors for real-time surveillance of freshwater ecosystems - PhD

Cranfield University Original Source
Award

£20,780 - £20,780

Deadline

Feb 25, 2026

Deadline passed
Location

United Kingdom

Applicants

individual

About This Opportunity

Cranfield University is excited to invite applications for a PhD studentship focused on developing and validating innovative origami-paper eDNA sensors with community scientists for the rapid detection of chemical and microbial contaminants in rivers. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research on human-environment interactions in freshwater ecosystems. The successful candidate will work collaboratively within a dynamic team, utilising cutting-edge technology to create low-cost and user-friendly sensors for deployment by citizen scientists. The project will involve co-designing the sensors with public stakeholders to ensure usability and accuracy, as well as conducting field tests to validate their effectiveness. Additionally, the research will explore the economic viability of these sensors to enhance real-time data collection and improve monitoring practices, and the social factors that influence their uptake. This studentship offers a unique opportunity to engage in ground-breaking research with practical applications, promoting community involvement in detecting chemical and biological contaminants and monitoring biodiversity.

Duration 48 - 49 mo
1 award

Who Can Apply

Region
United Kingdom
Citizenship
United Kingdom
Residency
United Kingdom
Project in
United Kingdom
Applicants
individual
Priority for
women_in_stem, racial_minorities, lgbtq, disabled, first_generation, low_income

Application Details

Stages

  1. 1 single_stage

Required documents

cv research_proposal transcripts

Additional benefits

  • training
  • networking
  • mentorship

Restrictions

  • reporting_requirements

Post-award obligations

  • acknowledge_funder