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KTP Associate - Data Scientist Research Associate
School of Mathematics, Statistics & Actuarial Science
Salary: £35,000 to £40,000 inclusive of KTP supplement
Grade: Grade 6
Post Type: Full Time
Contract Type: Fixed Term - 12 Months
Release Date: Friday 17 June 2022
Closing Date: 23.59 hours BST on Tuesday 28 June 2022 (unless
Interview Date: Friday 08 July 2022
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:
Upscale existing Bayesian hierarchical models developed by the academic
team and their adaptation from single to multi-species within an eDNA
context over multiple samples.
Embed the knowledge from this KTP into the Data Analysis Team to be
propagated through the Products and Commercial Teams into new decision-
support tools for NatureMetrics' clients
Work at the cutting edge of biodiversity monitoring using eDNA surveys and
develop a complete modelling and software solution by implementing the new
model, algorithm and study design tool in accessible and user-friendly
Work closely with the Business Development and Products Teams to guarantee
that the developed models and corresponding software fit business needs
and all new market opportunities developing from this project are fully
exploited, especially regarding input to materials to market and
communicate products, highlighting needs for clients to invest in enhanced
products (WP 3.1).
To be successful in this role you will have:
A PhD (or equivalent qualification) in statistics, data science, or
closely related disciplines that includes substantial development of new
statistical methods for ecological data and associated inferential tools
Experience in developing new statistical methods for ecological data, and
in particular DNA-based survey data, within a Bayesian framework
(particularly hierarchical models) and associated MCMC algorithms
A recent track record of publication or papers in preparation in leading
international journals or conferences of statistical models for ecological
data, and especially DNA-based survey data
Excellent communication skills to deal with a variety of people at
different levels of seniority
Leadership attributes and be prepared to take control of all aspects of
the KTP project throughout its duration
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:
Further details: Job Description Additional Information
Please note that we prioritise applications from current University of Kent
redeployees. We will let you know if this post is to be filled by a redeployee
as, in this instance, your application will unfortunately not be taken
Applications must be made via the University's online application system; CVs
or details sent directly to the department or via email cannot be considered.
The University of Kent values diversity and promotes equality at all levels.
Due to the current COVID-19 outbreak, interviews may take place remotely.