PhD-studentship in Applied Mathematics / Quantitative Ecology: Wind-Assisted Dispersal of Insect Tree Pests: An Interdisciplinary Modelling and Ecological Study

Newcastle University

Location: Newcastle

Salary: £21,805 per year
Contract: Contract
Working hours: Full-time
Posted: 12 hours ago

Award Summary

100% home fees covered, and a minimum tax-free annual living allowance of £21,805 (2026/27 UKRI rate), plus a RTSG to cover additional research costs/travel.

Overview

This interdisciplinary PhD project will bring together mathematics and ecology to assess the risk of invasive tree pests being transported into Great Britain by wind. While biosecurity measures largely focus on trade-related pathways, long-distance wind-borne dispersal may also represent a significant introduction route for insects. This project aims to develop and apply quantitative methods to assess wind-borne dispersal risk for a range of pests of concern to GB forestry, building on recent work on dispersal of the European spruce bark beetle.

The studentship will investigate:

Which tree pests on the Pest Health Risk Register may be aerodynamically capable of long-distance semi-passive wind-assisted dispersal.
How constraints on flight duration and temperature thresholds for flight initiation influence the potential source range of representative aerodynamically capable pests.
Whether insect tree pests of concern to the UK can be classified by likely flight dynamics, and how these classes correspond to taxonomic and ecological groupings.
The development and exploration of models that integrate biological understanding with atmospheric dispersion models to predict spatio-temporal spread of wind-dispersed invasive pests.

The student will gain interdisciplinary skills in mathematical ecology, entomology, aerodynamics, atmospheric modelling, and epidemiology. The project may include opportunities for laboratory-based work to support model development and validation. The ideal candidate will have a strong quantitative background and an interest in coding and applying modelling approaches to real-world biosecurity challenges.

Number Of Awards

1

Start Date

21st September 2026

Award Duration

3.5 years

Application Closing Date

#s1-Gen

The student will gain interdisciplinary skills in mathematical ecology, entomology, aerodynamics, atmospheric modelling, and epidemiology. The project may include opportunities for laboratory-based work to support model development and validation. The ideal candidate will have a strong quantitative background and an interest in coding and applying modelling approaches to real-world biosecurity challenges.

100% home fees covered, and a minimum tax-free annual living allowance of £21,805 (2026/27 UKRI rate), plus a RTSG to cover additional research costs/travel. Overview This interdisciplinary PhD project will bring together mathematics and ecology to assess the risk of invasive tree pests being transported into Great Britain by wind. While biosecurity measures largely focus on trade-related pathways, long-distance wind-borne dispersal may also represent a significant introduction route for insects. This project aims to develop and apply quantitative methods to assess wind-borne dispersal risk for a range of pests of concern to GB forestry, building on recent work on dispersal of the European spruce bark beetle. The studentship will investigate:

Which tree pests on the Pest Health Risk Register may be aerodynamically capable of long-distance semi-passive wind-assisted dispersal.
How constraints on flight duration and temperature thresholds for flight initiation influence the potential source range of representative aerodynamically capable pests.
Whether insect tree pests of concern to the UK can be classified by likely flight dynamics, and how these classes correspond to taxonomic and ecological groupings.
The development and exploration of models that integrate biological understanding with atmospheric dispersion models to predict spatio-temporal spread of wind-dispersed invasive pests.

2 temporary Scientific jobs in Hexham, Northumberland