Environment
The Mathematical Modelling of Infectious Diseases Unit at Institut Pasteur was created in November 2013 and is directed by Dr Simon Cauchemez.
The research focus of the Unit is to develop state-of-the-art mathematical and statistical methods to tackle the many challenges epidemiologists and microbiologists face when analysing infectious disease data.
Our primary focus is the study of infectious disease dynamics, both in long-term endemic settings and in outbreaks. We aim to better understand how pathogens spread in human populations with a view to support policy making and optimize control strategies. These analyses benefit from a strong network of collaborators in the field (in particular within the large International Network of Pasteur Institutes that consist of 32 institutes spread across the world) but also of strong connections with other Centres of Excellence in mathematical modelling. Our approach is therefore highly multidisciplinary, looking at infectious diseases through multiple perspectives (epidemiology, surveillance, Public Health, policy making, microbiology), multiple scales and multiple data streams.
More details can be found at www.pasteur.fr/en/research/infection-epidemiology/units-groups/mathematical-modelling-infectious-diseases.
Job description
We are seeking three postdocs to work in close collaboration with French agencies in charge of human (ANSP) and animal health (ANSES) with a view to strengthen the contribution of modelling in the detection, monitoring and management of epidemics in France. The selected candidates will develop innovative statistical and modelling methods to analyse French surveillance data on infectious diseases.
Two postdocs will work with ANSP to improve our ability to predict epidemics in human populations and provide real-time support during outbreaks of emerging infectious diseases to inform the response of the French government. The postdocs will work on a broad portfolio of projects covering a wide range of pathogens (influenza, zika, measles…) as well as different types of surveillance data (Sentinel surveillance, new surveillance systems monitoring all admissions in French hospitals, field studies and outbreak investigations).
One postdoc will work with ANSES to develop real-time modelling tools that can be deployed during epizooties (e.g. bluetongue, bTB or FMD) to advice on optimal surveillance and control strategies. The postdoc will be supervised by Benoit Durand (ANSES) and Simon Cauchemez (Institut Pasteur) and he/she will be primarily based at ANSES.
The postdocs will be expected to develop state-of-the-art statistical methodology that may involve Markov Chain Monte Carlo Sampling (MCMC), Sequential Monte Carlo sampling, Particle MCMC, Approximate Bayesian Computation or tree reconstruction techniques. The exact projects the successful applicants will undertake will be determined in discussion with the team, taking into account the applicants’ interests and experience.
Applicants will be given a one-year contract with possibility to extend it for another 2 years, should both parties agree.
Interested candidates should contact email Ana de Casas (ana.de-casas@pasteur.fr) with a CV, statement of interest and two references (to be sent directly by referees). The deadline for applications is 7 November 2016.
Salary: Depending on education and experience.
Location: Given the collaborative nature of the work, the applicants will be expect to spend a proportion of their time at ANSP (for the two postdocs working on human diseases) and at ANSES (for the postdoc working on animal diseases).
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, 28 rue du Docteur Roux, 75724 Paris Cedex 15, France.
- Unité Epidémiologie des maladies animales infectieuses, ANSES, 14 rue Pierre et Marie Curie, 94700 Maison-Alfort.
- ANSP, 12 rue Val d’Osne, 94419 Saint Maurice.
Person specification:
- Research experience of working with mathematical and/or statistical models.
- A strong interest in infectious disease epidemiology.
- Ability to collate and analyse data, interpret and present results to a high standard using a range of specialised research techniques.
- Programming experience in C, C++ or Java.
- Knowledge of a statistical programming language (preferably R).
- Excellent verbal and written communication skills. The working language of the laboratory is English.
- Experience in communicating research findings to a non-specialist audience.
- Ability to work independently but also as part of a larger interdisciplinary research team.
- PhD in one of the following areas: infectious disease epidemiology, mathematics, statistics, physics, computer science, population biology or a similarly quantitative discipline.