Research Fellow in Mathematics(UK Sponsorship)

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Uk
April 6, 2026
Full Time Permanent
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Job Description

About the Role

The University of Sussex is seeking a Research Fellow in Mathematics to contribute to an exciting interdisciplinary project exploring the ecological and epidemiological dynamics of tick-borne diseases.

This role focuses on understanding how environmental change and urbanisation influence the spread of pathogens carried by ticks. You will apply advanced mathematical modelling techniques to investigate how interactions between ticks, hosts, and pathogens evolve across different ecological landscapes.

Working within the Department of Mathematics, you will contribute to a major international research collaboration aimed at improving our understanding of disease risk and informing public health and environmental management strategies.

Your Key Contributions

Develop and analyse metapopulation and network-based models
Explore ecological systems involving hosts, vectors (ticks), and pathogens
Integrate environmental, biological, and social data into modelling frameworks
Work with complex spatial and temporal datasets from international collaborators
Identify drivers of disease transmission and highlight potential intervention points
Collaborate with researchers across the UK and the United States

Research Project Context

This role forms part of a four-year international project examining the eco-social dynamics of tick-borne diseases across environmental gradients.

The project is jointly funded by UK and US research bodies and involves collaboration with:

  • University of Bath
    Columbia University

There is potential for the successful candidate to extend their involvement by transitioning to a related position at the University of Bath for a further two years.

About You

We are looking for a motivated and analytical researcher with a strong interest in applying mathematics to real-world biological and environmental challenges.

Essential requirements:

  • A PhD in Mathematics (or near completion at the time of appointment)
    Background in mathematical biology, epidemiology, or dynamical systems
    Experience working with large or complex datasets
    Proficiency in programming (e.g. Python, MATLAB, or R)

Desirable qualities:

  • Ability to work independently and collaboratively
    Strong communication skills for interdisciplinary research
    Interest in ecological modelling and public health applications

About the School

The School of Mathematical and Physical Sciences at Sussex is known for combining high-quality teaching with internationally recognised research.

It provides a collaborative and supportive environment where researchers can thrive, innovate, and contribute to global scientific challenges. The School also maintains strong links with external partners to maximise the real-world impact of its research.

Why Join Sussex?

Located near the South Downs National Park, the Sussex campus offers an inspiring setting for both work and life. With excellent transport links, including Falmer station nearby, commuting is convenient.

Staff benefit from:

  • Flexible working arrangements
    A welcoming and inclusive culture
    Opportunities for career development
    Strong interdisciplinary collaboration

Application Requirements

Applicants should submit:

  • An academic CV
    A personal statement (maximum 500 words) outlining research experience and interests
    Academic transcripts
    Contact details for two referees
    Completed application form

For informal enquiries, please contact Prof Konstantin Blyuss.

Eligibility & Visa Information

This position qualifies for Skilled Worker visa sponsorship (subject to meeting criteria) and may also be eligible under the Global Talent visa route.

Applicants requiring sponsorship should review the following official UK government guidance:

Please note that some applicants may require ATAS clearance before starting the role.

All work associated with this position must be undertaken within the UK.

Equality, Diversity and Inclusion

The University is committed to building a diverse academic community and encourages applications from underrepresented groups in STEMM disciplines.

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