About the Role
Company: INRAE Occitanie-Toulouse
Position: Research Engineer in Remote Sensing and Artificial Intelligence Applied to Agroecology
About INRAE
The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a public research establishment bringing together around 12,000 staff across 272 research, service, and experimental units in 18 locations 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, and Activities
You will be based at the EcoSystèmes et Sociétés en Montagne (LESSEM) laboratory in Grenoble—a multidisciplinary unit integrating plant and forest ecology, social sciences, and agronomy and economics. You will join the RESTORE team, which conducts research in restoration ecology to inform public policy and develop nature-based solutions. RESTORE 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 national research project AI-Herbage, funded by the PEPR Agroécologie et Numérique program and led by a consortium including CIRAD, CNRS, INRAE, Inria, and Institut Agro. AI-Herbage aims to develop a complete data monitoring, analysis, and decision-support chain to improve grassland, pasture, and livestock management. Ultimately, this work will support more efficient and sustainable grassland management, reduce input use, and enhance biodiversity monitoring.
Your Mission Will Include:
Designing and testing the feasibility of a grass growth observation platform for agriculture in the French Alps;
Designing databases to harmonize 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 gathered during airborne and satellite campaigns in alpine study areas;
Coordinating simultaneous data acquisition campaigns for multi- and hyperspectral very high-resolution satellite and drone imagery alongside field surveys (floristic, biomass, GNSS RTK topography);
Developing image processing methods (photogrammetry, radiometry) for multi- and hyperspectral data applicable 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.
Specific Working Conditions:
Work in mountainous areas.
Required Education and Skills:
Master’s degree or Engineering degree (Bac+5)
Desired Knowledge:
Expertise in collecting, processing, and analyzing very high-resolution spatial airborne data (drones and satellites: Pleiades, NEO, Spot 6-7), LiDAR, and radar;
In-depth knowledge of very high-resolution remote sensing (THRS), image and signal processing, photogrammetry, and the design and training of deep learning AI models for point cloud and multi/hyperspectral image classification.
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 in interdisciplinary research teams, collaborating with field technicians, engineers, and researchers;
Ability to work autonomously, with rigor and critical thinking;
Strong teamwork and communication skills;
Ability to disseminate research results, including scientific writing.
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 compensatory time-off (RTT) days (full-time);
Parental support: CESU childcare vouchers, leisure benefits;
Skills development: training, career guidance;
Social support: counseling, social aid and loans;
Leisure and vacation benefits: holiday vouchers, preferential-rate accommodations;
Sports and cultural activities;
Collective catering.
How to Apply:
Submit your CV and cover letter.
Legal Notice:
As a public research establishment, INRAE is subject to the French Civil Service Code, including obligations of neutrality and respect for secularism (laïcité). As such, in the performance of their duties—whether or not in public contact—employees must not manifest their religious, philosophical, or political beliefs through behavior or attire. For more information: servicepublic.gouv.fr (https://www.servicepublic.gouv.fr).