RobustInfer - Postdoctoral position

Postdoctoral position - Inference and mechanistic models for large-scale transmission of animal diseases

Position start date: early 2022
Duration: ~18 months

We are seeking for a postdoctoral research scholar skilled in statistical inference and/or mechanistic modelling and/or phylodynamic to join our team in Nantes, France (DYNAMO team, BIOEPAR Research Unit, INRAE). This position will primarily involve working on the development of inference procedures incorporating various types of data (demographic and epidemiological survey, contact network, phylodynamic information).

The work will address some (or all) of the following points:

  1. The development of inference procedures incorporating classical epidemiological data and phylodynamic information, to estimate key parameters of mechanistic epidemiological models at large scale
  2. The development of a likelihood-free inference approach based on optimal transport distances
  3. The development of summary statistics for ABC-like methods, in particular through the determination of the most relevant aggregation scales, depending on the characteristics of the systems being studied.
  4. Determining the quantity and quality of data required for the estimation of key parameters/processes when available data are insufficient.
  5. Application to epidemiological systems of interest studied within the team for which extensive data are available.

The project will include work on synthetic data and the application on an epidemiological system of interest studied within the team (BVD - bovine viral diarrhea or bovine paratuberculosis), for which a model and observed data are already available. The available dataset includes full demographic cattle data, comprehensive animal movement data, and epidemiological survey at the individual or farm level over a nine-year period (more new data to come). Phylodynamic data are currently being collected.
The research tasks and approaches used in this project may be tailored to the interests and skills of the selected candidate.

Environment: The DYNAMO team conducts modelling research in population dynamics and animal epidemiology that aims to better understand and predict the spread and persistence of pathogens in animal populations, and to identify efficient and targeted control strategies. Such complex biological systems are studied at the within-host, between-host, and metapopulation scales, also using in the latter case trade network data and graph theory. The group’s research work focuses mainly on infectious diseases of cattle and swine, as well as on vector population and arboviruses dynamics.
You will work in a group with a strong background in epidemiology, disease spread and mathematical modelling, inference methods for mechanistic models, networks analyses, and agent-based simulation. The group is composed of four permanent researchers and two permanent engineers, as well as postdoctoral fellows, PhD students, and master students.
As part of the project, you may have to work in collaboration with partners from the DYNAMO team.
Access to high-powered computing is available, and the team’s engineers will be able to provide methodological and technical assistance.

Candidate must have a Ph.D. degree in a relevant quantitative discipline or closely related field. Previous experience working with inference methods (particularly likelihood-free approaches as ABC methods) and phylodynamic data will be highly appreciated. Practical experience in building mechanistic models would be an asset. Good computer programming skills will be required (Python and/or C++ preferably), and experience of working with Git and using cluster computing resources would be a plus. The candidate should have excellent communication skills and the ability to work in collaboration.

This post is part of a project funded by the region Pays de la Loire, and will cover salary, computer equipment and travel costs for the project, publications, etc.

Salary: between €2,300 and €2,900 per month gross depending on previous experience.

To apply: please submit your application by email to Dr. Gaël Beaunée at [email protected], please include in your application the following materials:

  1. a one-page cover letter describing your research interests and background, why you are interested in this position, and your career goals,
  2. a curriculum vitae or resume,
  3. the contact information (name, position, relationship to applicant, email, and phone number) of two references.

Should you have any queries on the job offer or the working environment, please contact Gaël Beaunée ([email protected]).