Junior research scientist in statistics of stochastic processes

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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

In the MISTEA unit based in Montpellier, we develop original methods in Mathematics, Computer Science and Statistics applied to the Environment and Agronomy. Our main objective is to contribute to a better understanding of, and decision-making on, issues related to agriculture and the management and protection of natural resources. The MISTEA lab has about fifty members, including about thirty permanent members, divided into three research groups, Probability and Statistics, Dynamical Systems and Computer Science, and a software production cell, OpenSILEX.
You will have a close working relationship with members from the Probability and Statistics Axis (around fifteen persons) and from the Dynamical Systems Axis (around 10 persons) who have particular expertise in algorithms and stochastic processes, statistics, filtering and observers, optimization and segmentation. In particular, we are working on issues in digital breeding, bio-processing and phenotyping based on the processing of sensor data, creating a need for online processing algorithms, predicting relevant quantities indirectly, taking into account known physical models, identifying changes in noisy data or adapting methods to discrete or continuous temporal data. You will develop research activities in statistics of stochastic processes. Your mission will involve the study and implementation of modern numerical methods for the inference and calibration of random dynamic models for data from livestock and agricultural sensors. These random dynamic models include Markov processes, diffusion processes, hidden Markov processes and deterministic models.
You may be required to estimate latent variables, such as change-point or mixing model structures. These models can be inferred using Bayesian, non-parametric or high-dimensional statistical methods. To improve our understanding of agricultural systems and provide numerical tools for decision making, you will contribute to the implementation of stochastic algorithms on these subjects using adapted learning methods (intensive computing, modeling, simulation...). You will benefit from the wide network of collaborations already established at MISTEA and expand it to different levels. You will participate in ongoing projects and develop your own ones to mobilize expert knowledge, increase the quality and robustness of predictions, and access unobservable quantities.

Training and skills

You hold a PhD degree or equivalent. Skills and research experience in statistics of stochastic processes are highly recommended.
You are expected to have a good knowledge of recent methods in process statistics: adaptive methods for estimating parameters (functional or not) of stochastic processes, inference of hidden Markov models or latent variable models, algorithms for detecting breakpoints in diffusive or jump processes, variational approaches... Knowledge of Bayesian statistics and associated particle algorithms would be appreciated.
You will be expected to be able to implement some of the above methods on current MISTEA projects. An interest in biological or environmental issues and experience of real-life applications would be a plus. The ability to discuss and collaborate with specialists in applied disciplines is expected.
You enjoy teamwork and you have good interpersonal skills. You show initiative, autonomy and dynamism.
Fluency in English is desirable, as is long-term international experience: successful candidates who have not already had such experience will be encouraged to spend a period abroad, co-designed with the host team, at the end of the 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 Application guidelines CRCN 2025 pdf - 3.93 MB
2. I write down the profile number CR-2025-MATHNUM-2
3. I apply GO