Mathematical Disease Modeler

3 weeks ago


London, Greater London, United Kingdom FSID - Food Systems Innovation & Delivery Full time
Job Overview

We are seeking a highly skilled Mathematical Disease Modeler to join our team at FSID - Food Systems Innovation & Delivery. The successful candidate will be responsible for developing and deploying landscape-scale stochastic spatial epidemic models for crop disease and pest outbreak prediction, surveillance, and management.

The ideal candidate will have a strong mathematical and statistical background, specifically in relation to Bayesian parameter estimation techniques. They will also have experience with high-performance computing, geostatistical analysis, and optimisation algorithms.

We are looking for a candidate who is passionate about real-world impact and has a strong interest in user-centric approaches and product development.

  • Develop and deploy landscape-scale stochastic spatial epidemic models for crop disease and pest outbreak prediction, surveillance, and management
  • Collaborate with stakeholders to translate their needs into actionable model-based solutions for outbreak monitoring and management
  • Apply Bayesian parameter estimation techniques to parameterise models, improve model accuracy, and account for uncertainty in disease dynamics
  • Review the scientific literature and work with partner organisations to identify datasets to parameterise epidemic spread and management interventions
  • Work with software developers to optimise the deployment of simulations on high-performance computing infrastructure
  • Develop optimisation algorithms to improve the efficacy of limited surveillance capacity
  • Communicate complex modelling techniques and results to non-technical stakeholders

Requirements

  • PhD/DPhil in applied mathematics, statistics, mathematical epidemiology, ecological modelling, or another relevant discipline
  • Specialist knowledge in parameter estimation, infectious disease modelling, and epidemiology
  • Strong modelling and computational skills, including experience with high-performance computing
  • Strong programming skills in Python/R and (ideally) C++
  • Experience with geostatistical analysis
  • Experience with optimisation algorithms
  • Interest in user-centric approaches and product development
  • Familiarity with agile development practices


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