Post-doctoral researcher in statistical inference for epidemiological models

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INRAE presentation

The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.

Work environment, missions and activities

You will be welcomed in the BioEPAR research unit, located in Nantes, as part of the Dynamo team. You will join a team of researchers working on mechanistic models for the spread of animal diseases. Alternatively, you can also join the Dynenvie team in the MaIAGE research unit, located in Jouy-en-Josas, near Paris. 

Your mission will be to develop and apply advanced likelihood-free statistical inference methods to improve the calibration of mechanistic epidemiological models. Indeed, mechanistic dynamic models are essential tools for anticipating and controlling the spread of infectious diseases at large scales. However, their performance critically depends on effective calibration using empirical data that are often complex, incomplete, and heterogeneous (epidemiological, serological, and genomic). There is currently a lack of robust methodologies to efficiently integrate such diverse data sources into complex epidemiological models. This project aims to develop likelihood-free statistical inference methods tailored to large-scale epidemiological models, using bovine viral diarrhoea virus (BVDV) as a case study. BVDV is an endemic disease characterized by silent spread through persistently infected animals, making it particularly suitable for methodological advances in data integration and transmission reconstruction.

You will be more specifically in charge of:

1. Development of inference methods: you will design and evaluate summary statistics for heterogeneous data integration, as well as implement and compare likelihood-free approaches (e.g., ABC-SMC, ABC-RF, Wasserstein-ABC, NPE) with respect to accuracy and computational efficiency.
2. Data requirements and surveillance design: you will identify the minimal quantity and quality of data required for reliable model calibration and assess how surveillance strategies (frequency, type, and coverage) impact inference performance.
3. Application to real-world data: you will develop a multi-strain mechanistic model for BVDV transmission in France, incorporating observation and sampling processes. You will also calibrate the model using the developed framework and reconstruct transmission patterns.

Training and skills

Recommended training: A PhD in statistics, applied mathematics, computational biology, epidemiology, or a related field

Desired knowledge: strong background in statistical inference, ideally including Bayesian methods and/or likelihood-free approaches

Appreciated experience: spatial or network-based modelling; genomic data analysis or phylodynamics.

Skills: Proficiency in programming (e.g., R, Python, or C++); interest in infectious disease modelling and data integration; strong analytical, problem-solving, and communication skills; ability to work both independently and collaboratively in an interdisciplinary environment.

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
- parenting support: CESU childcare, leisure services;
- skills development systems: training, career advise;
- social support: advice and listening, social assistance and loans;
- holiday and leisure services: holiday vouchers, accommodation at preferential rates;
- sports and cultural activities;
- collective catering.

How to apply

I send my CV and my motivation letter