The project sits at the interface of pathogen genomic epidemiology, statistical inference, and open-source software development and would be an excellent fit for someone excited about developing new methods with real public health impact.

Inferential frameworks combining pathogen genomic and epidemiological data have transformed transmission chain reconstruction for viral and bacterial pathogens, but these approaches cannot be transferred directly to malaria. The unique biology of Plasmodium parasites makes genetic signals of transmission non-linear, requiring new approaches for inference and to interpret genetic data in relation to transmission, importation, persistence, and resurgence.

You will be joining the recently established TAGUA group (https://shaziaruybal.github.io/TAGUA) at ISGlobal led by Dr Shazia Ruybal-Pesántez, to develop a network-based inferential framework for reconstructing malaria transmission networks from epidemiological and genetic data. This will include i) model development and extension to accommodate multimodal serial intervals, undetected infections, and the complexity of malaria genetic data; ii) model testing through simulation and fitting to datasets from international partner studies; iii) open-source R package development and reproducible workflows.

We are looking for:

• A PhD (awarded or near completion) in statistics, epidemiology, mathematics, or a related quantitative field
• Demonstrable experience developing, fitting and validating likelihood-based or Bayesian models
• Depth in at least one of: Bayesian inference and computation (e.g. MCMC), infectious disease outbreak inference or network science
• Strong programming skills in R or Python, with reproducible coding practices
• Lead author peer-reviewed modelling papers or equivalent major research output

Experience in infectious disease dynamic modelling, pathogen genomic epidemiology (e.g., phylogenetics), simulation-based model validation, and/or track record of open science (e.g. shared code, R packages) will be highly valued.

Prior epidemiology or pathogen genetics experience is not required, but genuine interest in these areas is important.

Interviews will happen on a rolling basis - applications will close on 30th October or until the position is filled.