Job

We are hiring a postdoctoral researcher to work full-time on the DiscoReel project. The postdoc will work on developing machine and deep learning methods for epidemic modeling, integrating them with mechanistic models and focusing on foundation models.

We are opening an internship position at Inserm (Paris) to work on the causal analysis of PrEP uptake and sexual behavior change among MSM, as part of the PP-IMPACT project funded by ANRS-MIE.

Patterns of human mobility shape spatial contact networks that determine how respiratory pathogens spread and how well surveillance systems detect epidemic activity. Mathematical models can combine large-scale mobility data with epidemiological surveillance to estimate and forecast epidemic risk (see this for example).

We are looking for an intern to join our research on devising and applying complex systems physics and deep learning methods to finding low-dimensional interpretable representations of realistic epidemic processes. Python skills, possibly with previous experience with pytorch, and a strong ability to learn are essential.

We are looking for an intern to join our research on integrating large-scale, high-resolution mobility data to build exposure risk maps for infectious disease epidemics. The data will be provided by Meta - see this for how we used similar data.

This position has been filled We are looking for an intern to apply foundation models to modeling epidemics and informing public health strategies (e.g., immunization campaigns, mobility restrictions). Candidates will be 1st-year or 2nd-year master students in computer science, machine learning, physics applied mathematics, engineering or other relevant fields.