Junior research scientist in data modeling and assimilation

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INRAE presentation

INRAE, the French National Research Institute for Agriculture, Food, and Environment, is a public research organization bringing together 12,000 employees across 272 units in 18 centers across France. As the world’s leading institute specializing in agriculture, food, and the environment, INRAE plays a key role in supporting the necessary transitions to address global challenges.

Faced with population growth, food security challenges, climate change, resource depletion, and biodiversity loss, INRAE is committed to developing scientific solutions and supporting the evolution of agricultural, food, and environmental practices.

INRAE is recruiting researchers by open competition and offering permanent position.

Work environment, missions and activities

You will carry out your work within the MaIAGE Unit, located at the Jouy-en-Josas research center and the Université Paris-Saclay. The unit comprises four research teams and a bioinformatics platform. You will join the Dynenvie team (9 permanent staff), which develops research in dynamic modeling and statistics applied to ecosystems, epidemiology, and agronomy, with a particular interest in spatio-temporal dynamic phenomena spanning scales from within-host to metapopulation levels. Its methodological work is structured around three main research axes: modeling of these phenomena, development of inference methods adapted to the heterogeneity and dependency structure of collected data, and development of original work at the interface between modeling and statistics. You will be primarily involved in the first and third of these axes.
The construction and parameter estimation of complex, nonlinear, high-dimensional dynamic models from experimental data represent a major methodological challenge, requiring research at the interface between mechanistic modeling, statistics, and (deep) learning. You are a specialist in modeling (ODEs, PDEs, hybrid deterministic/stochastic models) with a strong interest in the analysis, estimation, and integration of data within such models. You will contribute to the development of dynamic models and inference and data assimilation methods suited to contexts where data are often high-dimensional and heterogeneous. The conceptual framework may include Bayesian estimation, metamodel-based approaches (splines, Gaussian processes, deep neural networks), combined with inverse problem solving or filtering techniques. You may also contribute to the development of innovative approaches for data preprocessing and reduction, aimed at their assimilation into models. Finally, you will contribute to or lead interface projects in domains of interest to INRAE—such as microbiology, epidemiology, or agroecology—in particular those contributing to the development of digital twins.
Within MaIAGE, your responsibilities will include: (i) developing original methods for the analysis, estimation, and integration of data into dynamic models; (ii) developing the associated algorithms; (iii) collaborating with researchers in modeling, data science, and other disciplines (e.g., microbiology, epidemiology, agroecology), and (iv) monitoring and contributing to advances in the state of the art within your field of expertise.
The scientific environment in the Paris region is very dynamic. You will take part in this ecosystem by building relevant collaborations to develop your research project. You will develop your own network of national and international collaborations necessary to support your research. Upon arrival, you will participate in ongoing projects within your team - for example, one at the interface with microbiology, or another on digital twins, in collaboration with INRIA. You will be expected to take initiative in proposing new projects relevant to your research goals. You will further develop your expertise in data assimilation by contributing to the scientific activities at the interface between modeling and data science, both within the team and more broadly within the unit.

Training and skills

Competition open to candidates holding a PhD (or equivalent degree).
A specialization in applied mathematics, particularly in modeling and scientific computing (ODEs, PDEs), is strongly recommended. You have acquired expertise in data assimilation or parameter estimation (Bayesian statistics, metamodel-based methods such as kriging, splines, or neural networks, as well as filtering and inverse problems) and possess strong programming skills. You demonstrate scientific curiosity, adaptability, and a willingness to engage in work at the interface between modeling and statistics, including hybrid deterministic/stochastic models.
An interest in applied and goal-oriented research is highly desirable.
You are expected to have the ability to communicate and collaborate effectively with specialists from applied disciplines.
You enjoy teamwork and have excellent interpersonal skills. You show initiative, autonomy, and enthusiasm in your work.
Proficiency in English is required, as well as significant international experience: successful candidates who have not yet had such experience will be expected to undertake an international research stay at the end of their probationary year.

INRAE's life quality

By joining our teams, you benefit from:

- 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.

For international scientists: please visit your guide to facilitate your arrival and stay at INRAE. 

How to apply

1. I download the applicant guide Guide for applicants 2026 pdf - 1.41 MB
2. I write down the profile number CR26-MathNum-3
3. I apply GO