We are seeking to appoint two Postdoctoral Research Associates to undertake research in mathematical and computational modelling of plant disease spread and control within the Department of Plant Sciences, University of Cambridge, as part of the Theoretical and Computational Epidemiology Group.

Plant pests and pathogens are a major threat to agriculture and ecosystems, with losses estimated to reach up to 40% of global production. Addressing the challenges posed by pests and pathogens requires modelling approaches that integrate processes across the full invasion pathway - from entry and establishment through to spread and long-term management - and that support real-world decision-making by stakeholders and policy makers.

The successful candidates will develop and apply process-based modelling approaches to support plant health surveillance, risk assessment and control strategies, relevant to policy frameworks used by organisations such as EFSA and EPPO.

The posts form part of a large European consortium (led by the University of Warwick, with partners across academia and plant health agencies).

Two complementary positions are available:

Post 1: Research Associate (platform and framework development – PhytoPRISM)

This post will focus on the development of a pest-generic modelling framework for system-level analysis of plant pest risks.

The successful candidate will develop spatially explicit, stochastic modelling approaches that link processes across the invasion pathway, from introduction and establishment through to regional spread and management. These integrate
• natural and human-mediated dispersal
• environmental and climate drivers
• interacting phytosanitary interventions across the agri-value chain

A key aim is to build generalisable, reusable modelling tools and frameworks applicable across multiple pest systems (focusing on six high-profile case studies, including Xylella fastidiosa and pine wood nematode), and to integrate these into a policy-facing decision-support platform.

This role will particularly suit candidates interested in:
• building modular modelling frameworks,
• linking models across scales and processes, and
• understanding and predicting pest invasion dynamics across scales

Post 2: Research Associate (epidemiological modelling – grapevine pathogens and beyond)

This post will focus on the development and application of process-based, spatially explicit epidemiological models for plant pathogens, particularly vector-borne diseases of grapevine.

The successful candidate will develop and analyse stochastic models of spread across heterogeneous landscapes, integrating:
• host distribution and landscape structure
• vector dynamics and dispersal
• climate drivers
• surveillance and control strategies

The work will explicitly span scales from local transmission processes to landscape-level spread, with emphasis on mechanistic realism.

The role will include:
• model fitting and parameter estimation using empirical data
• simulation studies of detection, containment, and control
• development of models to support policy-relevant decision-making

Note: Candidates will be considered for both positions where appropriate.

Working environment and opportunities

The posts are based in the Theoretical and Computational Epidemiology Group within the Department of Plant Sciences. The group has strong links to policy and regulatory communities, and access to major epidemiological and surveillance datasets through project partners and stakeholders.
The roles offer opportunities to:
• collaborate with leading European research institutes and plant health authorities
• contribute to policy-relevant modelling with real-world impact
• supervise undergraduate or postgraduate research projects (depending on experience)
• present work internationally and engage with stakeholders
• travel for project meetings, workshops, and conferences across Europe

General responsibilities (both posts)

Both roles will involve:
• development and analysis of mathematical and computational models
• integration of spatial and epidemiological data
• modelling across scales from biological processes to landscape spread
• collaboration within interdisciplinary European consortia
• preparation of research publications and project deliverables

We particularly encourage applications from candidates with experience in, or strong interest in, process-based spatial epidemiological modelling, although excellent candidates from related quantitative backgrounds are strongly encouraged to apply.