** Two >24-month postdoctoral positions in multi-scale modelling of antibiotic resistance transmission at Institut Pasteur, Paris **

Lab: Institut Pasteur, Paris, Epidemiology and Modelling of Antibiotic Evasion (EMAE) / Inserm UMR1018 / UVSQ / Paris Saclay

• Starting date: as soon as possible
  Applications will be reviewed on a rolling basis until the positions are filled. Candidates interested in both positions are welcome to say so and submit a single application.

• Description:
  We are recruiting two postdoctoral researchers to build the modelling and inference framework at the core of PRISM, a project focusing on the transmission of antibiotic resistance plasmids within and between individuals in small populations. The two positions are quantitative and complementary, one centered on simulation and one on statistical inference, and will be conducted in close daily collaboration.
  In Enterobacterales, antibiotic resistance transmission occurs at multiple scales: resistant bacteria spread between individuals, while the genes encoding resistance spread between bacteria via mobile genetic elements, such as plasmids. The objective of the PRISM project is to assess this joint phenomenon through the construction of multi-scale modelling frameworks and the analysis of large microbiological and epidemiological datasets. The resulting models will be used to predict which interventions are most effective for mitigating resistance spread.

PRISM is funded by Wellcome Leap's Resistance Networks program, an international consortium combining community cohorts, single-cell sequencing technologies and intervention testing across several continents. The two successful candidates will therefore work in close collaboration not only with one another, but also with the consortium. The project is fast-paced and built to deliver defined milestones against quantitative targets. We are looking for people who find this pace energizing rather than constraining. Details of the positions are provide below.

About Institut Pasteur: Institut Pasteur is a world-leading centre of research in infectious diseases and antibiotic resistance. Pasteur is a dynamic, international and collaborative research environment located central Paris.

• Start date: As soon as possible
• Duration: 24-36 months Location: Institut Pasteur, Paris, France
• Supervision: Prof. Lulla Opatowski

How to apply: Please send to lulla.opatowski@pasteur.fr, with the subject line "PRISM postdoc - simulation" or "PRISM postdoc - inference":
• a CV including publications and a link to any public code repositories
• a cover letter (max 2 pages) explaining your interest in the position and how your experience matches the profile
• contact details for two referees

• Position 1: Simulation
  The first position will lead the development of multi-scale transmission models incorporating a stochastic, individual-based simulator of plasmid dynamics. This model will represent plasmid dynamics amongst a network of bacterial lineages within the gut, coupled with a between-human transmission model in a small population (eg households). The objectives are to generate synthetic datasets to explore plasmid transmission under different hypotheses, to provide quantitative guidance to cohort partners on sampling design, and to evaluate intervention scenarios defined jointly with experimental partners.
  Profile
  Essential
  • PhD in mathematical epidemiology, computational biology, applied mathematics, physics, or a closely related quantitative field
  • Demonstrated experience building stochastic or individual-based dynamic models
  • Strong scientific programming (Python, Julia, R, C++), version control, and a commitment to reproducible, documented code
  • Capacity to work in teams
  • Capacity to work to deadlines within a collaborative consortium
  • Fluent scientific English
  Desirable
  • Experience with multi-scale or nested models
  • Familiarity with microbial ecology, antimicrobial resistance, or within-host population dynamics
  • Experience with network models or metapopulation structures
  • GPU-accelerated or high-performance computing experience
  • Prior contribution to released scientific software/package

• Position 2: Inference
  The second position will lead to the development of the inference framework used to analyse fine-grained longitudinal data collected in individuals. A hierarchical Bayesian framework estimating rates of within-host plasmid transmission will be built linking latent bacterial colonization states to several data layers simultaneously (to be adapted with partners: metagenomic abundance, isolate-level plasmid-host assignments, single-cell linkage). The within-host model will then be combined with a transmission inference framework for linked individuals in households. Depending on the candidate’s interests, several inference strategies may be explored and compared: likelihood-based Bayesian methods and amortized simulation-based inference using neural posterior estimation.
  Profile
  Essential
  • PhD in statistics, biostatistics, mathematical epidemiology, machine learning, or a closely related quantitative field
  • Solid grounding in Bayesian inference and hierarchical or mixed-effects modelling
  • Experience fitting mechanistic models to longitudinal or partially observed data
  • Strong scientific programming (R, Python, Julia, Stan, or equivalent), version control, reproducible workflows
  • Capacity to work in teams
  • Capacity to work to deadlines within a collaborative consortium
  • Fluent scientific English
  Desirable
  • Experience with MCMC for partially observed epidemic processes, data augmentation, or particle methods
  • Familiarity with simulation-based or likelihood-free inference
  • Experience with genomic or microbiome data
  • Background in infectious disease transmission modelling
  • Prior contribution to released scientific software/package