About the Role
Company: INRAE
The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a public research institution bringing together around 12,000 staff across 272 research, service, and experimental units in 18 centers throughout France. INRAE is a global leader in agricultural, food, plant, and animal sciences, aiming to develop solutions for multi-performing agriculture, high-quality food, and sustainable resource and ecosystem management.
Work Environment, Missions & Activities
You will be based at the Laboratory EcoSystèmes et Sociétés en Montagne (LESSEM) in Grenoble — a multidisciplinary unit integrating researchers in plant and forest ecology, social sciences, and agronomy/economics. You will join the RESTORE team, which conducts research in restoration ecology to inform public policy and develop nature-based solutions. The team combines field observations, species composition and trait analysis, remote sensing, and experimentation to design, assess, and improve restoration and compensation actions and their monitoring frameworks. Anchored in mountain territories — a privileged study area — the team also extends its work to various socio-ecological contexts in France and internationally.
This position is part of the AI-Herbage project, funded by the national research program PEPR Agroécologie et Numérique, led by a consortium including CIRAD, CNRS, INRAE, Inria, and Institut Agro. The project aims to develop a complete data monitoring, analysis, and decision-support chain to improve grassland, pasture, and livestock management — ultimately contributing to more efficient and sustainable grassland use, reduced inputs, and biodiversity monitoring.
Your Mission Will Include:
Designing and testing the feasibility of a platform for monitoring grass growth in French alpine agricultural systems;
Designing databases that integrate field surveys (biomass, floristic composition of permanent pastures) with very high-resolution spatial imagery in alpine environments;
Analyzing optical, LiDAR, and radar data using innovative AI-based image processing methods (deep learning, CNN classification);
Collecting, archiving, and processing images and data from airborne and satellite campaigns in alpine study areas;
Coordinating synchronized data acquisition campaigns (multi- and hyperspectral very high-resolution satellite/drones) and field surveys (floristic, biomass, GNSS RTK topography);
Developing image processing methods (photogrammetry, radiometry) for multi- and hyperspectral data, transferable to other study areas and broader alpine massifs;
Selecting and implementing AI/deep learning classification models to perform agro-ecological diagnostics at intra-parcel, massif, intra- and inter-annual (time series) scales;
Disseminating results through scientific publications and technical reports for project partners.
Special Working Conditions:
Fieldwork in mountainous areas.
Required Education & Skills
Education:
Master’s degree or Engineering degree (Bac+5)
Desired Knowledge:
Expertise in collecting, processing, and analyzing very high-resolution spatial airborne data (drones, Pleiades, NEO, Spot 6-7, LiDAR, radar);
In-depth knowledge of very high-resolution remote sensing (THRS), image and signal processing, photogrammetry;
Expertise in designing and training deep learning AI models for classification of point clouds and multi/hyperspectral imagery.
Preferred Experience:
Multi-sensor approaches (optical, radar, LiDAR remote sensing);
Time-series analysis for agro-ecological monitoring and diagnostics in mountain environments.
Key Competencies:
Programming skills (e.g., R, Python) applied to remote sensing;
Familiarity with AI image classification tools (CNN, YOLO);
Proficiency in GIS software (e.g., QGIS) and spatial databases;
Proficiency in photogrammetry software (e.g., Metashape, AMES Stereo Pipeline (ASP));
Experience working interdisciplinarily in research labs, collaborating with field technicians, engineers, and researchers;
Ability to work autonomously, with rigor and critical thinking;
Strong teamwork and communication skills;
Ability to publish scientific articles and communicate research outcomes.
Quality of Life at INRAE
By joining INRAE, you benefit (depending on contract type and duration) from:
Up to 30 days of annual leave + 15 RTD days (for full-time);
Parental support: CESU childcare vouchers, leisure benefits;
Skills development: training, career guidance;
Social support: counseling, social aid and loans;
Leisure & travel: vacation vouchers, preferential-rate accommodations;
Sports and cultural activities;
Collective catering.
How to Apply
Submit your CV and motivation letter.
As a public research establishment, INRAE is subject to the French Public Service Code, including obligations of neutrality and respect for secularism (laïcité). As such, in the exercise of their duties — whether or not in public-facing roles — staff must not manifest their religious, philosophical, or political beliefs through behavior or attire. > Learn more: fonction publique.gouv.fr (https://www.fonction-publique.gouv.fr)