Paris, 2nd December 2022
Postdoctoral and engineering positions in mathematical/statistical modelling of epidemics at Institut Pasteur, Paris
We are recruiting postdocs and engineers to contribute to research projects in the Mathematical Modelling of Infectious Diseases Unit, at Institut Pasteur in Paris. The candidates will be expected to work with and develop state-of-the-art statistical and mathematical methodology to improve understanding of epidemic dynamics and control. The exact projects the successful applicants will undertake will be determined in discussion with the team, considering the applicants’ interests and experience as well as ongoing collaborations of the team. A few exemplar projects include:
- PICREID project: We are part of the Pasteur International Center for Research on Emerging Infectious Diseases (PICREID), funded by NIH, with colleagues from Pasteur Institutes in Paris, Cambodia, Cameroun and Senegal. PICREID takes an inter-continental One Health approach designed to improve the capacity to respond rapidly and effectively to outbreaks. PICREID identifies factors influencing emergence and transmission at the virus, vector, and reservoir level leading to epidemics in suspected spillover conditions. The consortium concentrates on high priority RNA viruses with epidemic potential in Africa (Rift Valley Fever virus (RVFV), Crimean Congo Hemorrhagic Fever Virus (CCHFV)) and in Southeast Asia (dengue virus), as well as viruses (Disease X) identified from symptomatic surveillance or vector sampling. Postdocs working on this project will implement the following analyses:
- RVFV and CCHFV in West and Central Africa: The consortium is collecting serum samples in animals and in individuals with different risks of exposure (e.g. slaughtering house, farms, general population) in communities in Senegal and Cameroun, along with data on vectors. Postdocs will develop serocatalytic models to reconstruct from the data the history of viral circulation in animals and in humans (Hoze et al, Nature Com 2020) and characterize the animal-human interface accounting for the heterogeneity in individual exposures and the spatial structure of the data.
- Dengue in Cambodia: Detailed follow-ups of individuals in households with a dengue case are being done in Cambodia. The postdocs will develop Bayesian data augmentation strategies (Cauchemez et al, PNAS 2011) to probabilistically reconstruct transmission trees from the data, characterize the drivers of dengue transmission, dengue Antibody titer dynamics (Salje et al, Nature 2018) and the role of asymptomatic cases in transmission (Duong et al, PNAS 2015).
- Labex IBEID project: Postdocs working on this project will work closely with colleagues in Public Health agencies in France (Santé Publique France, Haute Autorité de la Santé) and abroad to develop statistical and mathematical models to better characterize and forecast the impact of epidemics and evaluate the effectiveness of pharmaceutical and non-pharmaceutical countermeasures, with a view to support decision making during epidemics. This includes methods to forecast epidemic dynamics of influenza, COVID-19 and other respiratory viruses such as RSV or methods to characterize and monitor population immunity against COVID-19.
- DURABLE project: This is a large European consortium that aims to provide high-quality scientific information in record time to support European HERA’s decision making in preparing for and responding to cross-border health threats and assessing the impact of countermeasures. It will coordinate a global collaboration, from pathogen detection, evolutionary analysis and threat characterisation, with One Health approach, to data and information collection and sharing, for optimal infectious disease threat response. Postdocs working on this project will develop multi-scale models that can integrate the mass of experimental and epidemiological data on emerging infectious disease threats generated by the consortium into real-time population-level risk assessments and forecasts.
We are looking for postdocs but also engineers with a strong expertise in programming. Successful applicants will collaborate with other members of the team and colleagues in partner institutions. They will be supervised by Dr Simon Cauchemez. Funding is available for 2 years, with possibility of extension for longer periods.
Interested candidates should contact email Cécile Limouzin (firstname.lastname@example.org) and Simon Cauchemez (email@example.com) with a CV, statement of interest and contact details of two referees that will be contacted directly after the interviews. The deadline for applications is Sunday 8th January 2023, with contracts starting as soon as possible.
The last few years have been marked by the emergence and spread of a number of infectious diseases across the globe. For example, outbreaks of Zika and chikungunya in the Americas, Ebola Virus Disease in West Africa and MERS coronavirus in the Middle East each resulted in substantial public health burden and received widespread international attention. More recently, the COVID-19 pandemic has had a devastating impact on populations across the world. These emergences have highlighted the many challenges faced by the public health community to anticipate, assess, manage and control these epidemics. In addition, established infectious diseases such as seasonal influenza, dengue or malaria keep on affecting hundreds of millions of persons each year.
In this context, the main research objective of the Mathematical Modelling of Infectious Diseases at Institut Pasteur is to develop state-of-the-art statistical and mathematical methods to analyze epidemic data, with the aim to increase our understanding of how pathogens spread in populations, assess the impact of interventions, support policy making and optimize control strategies. Our approach is highly multidisciplinary, looking at infectious diseases through multiple perspectives, multiple scales and multiple data streams. We work closely with public health agencies both in France and abroad.
During the COVID-19 pandemic, our research Unit has been heavily involved in the French response to the pandemic, providing modelling support to the French Ministry of Health, the Scientific Committee on COVID-19, the French CDC (Santé publique France), the French National Immunization Technical Advisory Group (Haute Autorité de Santé) to inform policy making and planning.
A few studies illustrating the diversity of our topics of interest:
- How to evaluate the prevalence and the performance of diagnostic tests when these tests are imperfect? The case of plague in Madagascar in 2017. ten Bosch et al, PLoS Biology 2022
- Development of an ensemble model to forecast COVID-19 hospitalisations in France. Paireau et al, PNAS 2022
- Estimating the burden of SARS-CoV-2 in France. Salje et al, Science 2020
- Using serocatalytic models to characterize the epidemic dynamics of Mayaro in French Guiana. Hoze et al, Nature Communications 2020
- Reconstructing antibody dynamics and infection histories to evaluate dengue risk. Salje et al, Nature 2018
- Early estimation of the risk of microcephaly associated with Zika infection in pregnant women. Cauchemez et al, Lancet 2016
Salary: Depending on education and experience.
Location: Mathematical Modelling of Infectious Diseases Unit, Department of Global Health, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris Cedex 15, France.
- Experience in 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.
- Good knowledge of the R statistical programming language.
- Programming experience in C, C++, Python or Java is desirable
- 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.
- For postdoc positions, PhD in one of the following areas: infectious disease epidemiology, mathematics, statistics, physics, computer science, population biology or a similarly quantitative discipline. For engineering positions: a master or Engineer degree in one of these disciplines.