Research Fellow in Mathematics(UK Sponsorship)

Job Description

Role Overview

The University of Sussex is recruiting a Research Fellow to contribute to a major interdisciplinary project focused on the ecological and social dynamics of tick-borne pathogens across environmental and urbanisation gradients.

This position sits within the Department of Mathematics and forms part of a large international collaboration funded by NSF (USA) and UKRI (UK). The project aims to improve understanding of how tick populations, host species, and pathogens interact across changing landscapes and how these processes influence human infection risk.

The role involves combining mathematical modelling, ecological theory, and real-world datasets to support disease risk prediction and management strategies.

Key Responsibilities

Mathematical & Computational Modelling

• Develop metapopulation and network-based models of tick-host-pathogen systems
  Integrate ecological processes into dynamic mathematical frameworks
  Analyse spatial and temporal patterns in disease transmission

Data Analysis & Interpretation

• Work with large, complex datasets from US and UK field studies
  Apply computational tools to identify environmental and social risk drivers
  Support modelling of urbanisation impacts on disease spread

Collaboration & Research Integration

• Work closely with partners at University of Bath and Columbia University
  Contribute to interdisciplinary research meetings and publications
  Translate modelling outcomes into practical insights for disease management

Scientific Output

• Publish research in leading peer-reviewed journals
  Present findings at international conferences
  Contribute to policy-relevant scientific communication

About You

You will be a mathematically trained researcher with strong quantitative and computational skills.

Essential requirements include:

• PhD (or near completion) in Mathematics, Applied Mathematics, Epidemiology, or Mathematical Biology
  Strong background in dynamical systems, ecological modelling, or epidemiological modelling
  Experience working with large datasets and computational analysis
  Proficiency in Python, MATLAB, or R
  Ability to work independently and within interdisciplinary teams
  Strong communication skills for academic and collaborative environments

A strong interest in environmental systems, disease ecology, or applied public health modelling is highly desirable.

About the Project

This role is part of a four-year international programme titled:
“Eco-social dynamics of tick-borne pathogens along urbanisation gradients: establishment, spillover, and management.”

The project investigates how environmental change influences disease risk, with a focus on:

• Urban expansion and biodiversity loss
  Tick-host interactions and pathogen transmission
  Human exposure risks and prevention strategies

It is a collaborative initiative involving UK and US institutions and aims to generate actionable insights for public health and environmental management.

About the School

The School of Mathematical and Physical Sciences at the University of Sussex is a research-intensive environment committed to advancing fundamental and applied science.

Key features include:

• Internationally recognised research in mathematics and physical sciences
  Strong interdisciplinary collaboration
  Active engagement with global scientific challenges
  Supportive and inclusive academic culture

The School holds a Bronze Athena Swan Award, reflecting its commitment to equality and diversity in science.

Working Environment & Benefits

The University is located near the South Downs National Park, offering a scenic and well-connected campus environment.

Staff benefit from:

• Flexible and hybrid working arrangements (where applicable)
  Access to high-performance computing and research infrastructure
  Cycle-to-work and sustainable travel schemes
  Strong interdisciplinary research culture
  Inclusive and collaborative academic environment
  Visa & Legal Information

This role may be eligible for Skilled Worker visa sponsorship, subject to eligibility criteria.

Please note: the role must be carried out within the UK.

Application Requirements

Applicants should include:

• Academic CV
  500-word personal statement outlining research experience and interests
  Academic transcripts
  Contact details for two referees
  Completed application form

Equality & Diversity Statement

The University actively encourages applications from women and individuals from Black and minority ethnic backgrounds, who are underrepresented in STEM disciplines.

Support is available for applicants requiring adjustments during the recruitment process.