Innovative statistical methods to understand and predict complex dynamic phenomena for agri-food transitions


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INRAE presentation

The French National Research Institute for Agriculture, Food, and the Environment (INRAE) is a public research establishment under the dual authority of the Ministry of Agriculture and the Ministry of Research. It is a community of 12,000 people with more than 200 research units and 42 experimental units located throughout France.

The institute is among the world leaders in agricultural and food sciences, in plant and animal sciences, and is 11th in the world in ecology and environment. INRAE’s main goal is to be a key player in the transitions necessary to address major global challenges. In the face of the increase in population, climate change, scarcity of resources and decline in biodiversity, the institute develops solutions for multiperformance agriculture, high quality food and sustainable management of resources and ecosystems.

Work environment, missions and activities

Nature and purpose of the research project to be developed and related activities :
The project aims to develop a new statistics theme within the Dynenvie team of the MaIAGE unit that will reinforce its positioning at the interface of statistics and dynamic models. Priority will be given preferably to new methods of statistical learning such as federated learning, transfer learning or causal inference. The originality of the project lies in the combination of this new theme and the characteristic multidisciplinarity of the Dynenvie team which already has solid skills in statistics and modelling, as well as recognised expertise in dependent data. Recent effective developments linked to modelling with causality and new learning methods have emerged in particular to improve the interpretability of methods. So, the objective of the recruitment project for the Dynenvie team is to i) develop new innovative statistical methods to understand and predict complex dynamic phenomena and ii) promote further the combination of the statistical and modelling components of the team to propose ambitious methods. The ultimate applications will initially concern long-term interdisciplinary collaborations of the Dynenvie team and could be subsequently expanded.

Nature and purpose of the teaching project :
The person recruited will be involved in the Master’s in mathematics at Paris Saclay University. There are strong historical links between INRAE and the Department of Mathematics within the Faculty of Orsay, in particular with regard to teaching applied mathematics. With the aim of reinforcing and expanding these links, the person recruited will teach more specifically in the new Master’s in Mathematics and Artificial Intelligence co-led by Orsay and CentraleSupelec where they can bring a complementary dimension from a point of view of applications in biology from the academic sector, most of the current applications being more in relation to the industrial sector.
Depending on the recruitment profile, new lessons on causality could be set up; this important theme is for the time being covered little in both teaching and research in the area. These lessons, which are of interest for several courses, could also be shared between several programmes such as the Master’s 2 in Statistics and Machine Learning or Mathematics for the life sciences.

Funding and related resources :
The person recruited will benefit from a host environment comprising funding for a PhD, a 2-year post-doc, and three Master’s work placements, as well as an installation package of 25 000 Euros over three years.

Training and skills

PhD or equivalent

PhD or equivalent

The desired profile is a person with a PhD in mathematics who has acquired in their early career as a researcher advanced skills in theoretical and/or computational statistics, preferably on themes linked to causality or federative or transfer learning, and having already conducted research at the interface with scientists from other disciplines, preferably life sciences.

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.

International scientists, please visit your guide to facilitate your arrival and stay at INRAE.

Type of contract

Tenure-Track Junior Professor Chair enables recruitment of scientists based on a research and teaching project that lasts three years. At the end of this period, and following an assessment of your scientific achievements and professional capabilities, you may obtain a full-tenure position as Research Director (DR2).

A research and teaching agreement will specify the path you will follow towards full-tenure and enable you to acquire the qualifications necessary to become a full-tenure Research Director in your field.

You have until April 12, 2024 to submit your application. Only candidates previously selected on file by the selection committee will be invited to the hearing.

Offer reference

  • Profile number: CPJ24-MATHNUM-1
  • Corps: Chaire de Professeur Junior
  • Category: A
  • Open competition number: 2


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