NatureMetrics is an innovative, science-based, women-led SME that commercialises environmental-DNA-based biodiversity monitoring solutions at scale. They are world leaders in delivering powerful, scalable biodiversity data collected safely and sustainably using environmental DNA. NatureMetrics works to develop end-to-end and automated tools for biodiversity detection in the field, to be used by non-experts.
We are seeking a PhD graduate who will be responsible for the development and integration of new statistical techniques for addressing two challenges associated with biodiversity surveys using environmental DNA: accounting for false negative and false positive readings, and optimising survey design. These techniques will improve the business’s decision-support tools for nature conservation and restoration, facilitating access to new markets.
Specifically, the aim of this KTP is to embed new knowledge and capabilities of Bayesian hierarchical statistical models developed by academics at the University of Kent and University College London. These models account for false positive and false negative errors in environmental DNA surveys. Through this KTP, these techniques will be integrated into NatureMetrics’ analysis workflows, enabling them to increase confidence levels around the presence/absence or abundance of surveyed biological communities (i.e. collections of species at a site) in downstream products. This will optimise the cost and effort needed to collect and analyse samples.
The Associate will be based at the NatureMetrics’ premises in Surrey and will work closely with the support and guidance of Dr Eleni Matechou, University of Kent, and Professor Jim Griffin, University College London. At the end of the fixed term contract, and upon successful completion of the project, there is a possibility that the role could become a permanent full-time position.
As a Research Associate you will:
To be successful in this role you will have:
Please see the links below to view the full job description and to apply for this post. If you require further information regarding the application process please contact the HR Team on CEMSHR@kent.ac.uk quoting ref number: CEMS-149-22