Research Fellow in Mathematics(UK Visa Sponsorship)

Uk
April 22, 2026

Job Description

Role Overview

The Department of Mathematics at the University of Sussex is recruiting a Research Fellow in Mathematical Ecology and Epidemiological Modelling. This position sits within an international, interdisciplinary research programme focused on understanding how tick-borne diseases spread across changing environmental and urban landscapes.

You will contribute to a major UK–US collaborative project examining how ecological systems, human activity, and environmental change interact to shape disease risk. The work combines mathematical modelling, ecological theory, and real-world data analysis to better predict and manage public health risks.

This research is part of a larger funding initiative supported by:

(UK Research and Innovation funding framework)
(National Science Foundation collaboration)

Research Focus

You will work at the interface of mathematics, ecology, and epidemiology, developing advanced models to study:

  • Tick population dynamics and host interactions
    Spread of tick-borne pathogens across landscapes
    Effects of urbanisation and environmental gradients
    Human infection risk patterns
    Intervention and disease management strategies

Your core responsibilities include:

  • Building metapopulation and network-based mathematical models
    Integrating ecological and epidemiological processes into computational frameworks
    Analysing large spatial and temporal datasets from international collaborators
    Identifying environmental and social drivers of disease emergence
    Supporting evidence-based public health and environmental management strategies

Collaboration & Project Environment

This role is embedded in a four-year international research programme titled:

Eco-social dynamics of tick-borne pathogens along urbanisation gradients: establishment, spillover, and management

Key partners include:

  • University of Sussex (UK)
    University of Bath (UK)
    Columbia University (USA)
    NSF-funded US research teams

There is also potential progression to a second phase of the project based at the University of Bath.

Candidate Profile

We are looking for a researcher with strong quantitative and computational expertise in applied mathematics and biological systems.

Essential requirements:
PhD (completed or near completion) in Mathematics, Applied Mathematics, or related field

Strong background in:

  • Mathematical biology
    Epidemiological or ecological modelling
    Dynamical systems or applied network theory
    Programming skills in Python, MATLAB, or R
    Experience working with complex datasets

Desirable attributes:

  • Interest in infectious disease ecology
    Experience in interdisciplinary research collaboration
    Ability to translate mathematical models into real-world applications
    Strong communication skills for academic and non-academic audiences

Relevant research and data governance guidance:

https://www.gov.uk/government/publications/data-protection-act-2018-overview
https://www.gov.uk/government/organisations/public-health-england

Working Environment

You will join a research-intensive and collaborative academic environment within the School of Mathematical and Physical Sciences, which is known for:

The School is committed to creating an environment that supports innovation, open scientific inquiry, and real-world impact.

Equality, Diversity & Inclusion

The University actively promotes inclusivity and encourages applications from underrepresented groups in STEM disciplines.

Key UK equality frameworks:

https://www.gov.uk/government/organisations/equality-and-human-rights-commission
https://www.gov.uk/government/collections/gender-pay-gap-reporting

Visa & Eligibility

This role is eligible for Skilled Worker visa sponsorship (subject to UK immigration requirements and salary conditions). It may also be eligible under the Global Talent visa route depending on individual circumstances.

ATAS clearance may be required depending on nationality and research area.

Employment Requirement

All work must be conducted within the United Kingdom in accordance with UK employment and research regulations.