Data Scientist - PostDoc (France)

THE ROLE

EarthDaily is looking for a PostDoc in remote sensing to join its Data Science team and develop innovative methods for processing multi-scale observations.

You will be involved in the development of methods in the framework of the PHENET European project WP3 (https://www.phenet.eu/en).

You will develop a multi-scale image harmonization framework for the analysis of automatically co-registered multi-resolution datasets (Sentinel-2, UAV, EarthDaily, on-field sensors).

The spectral and radiometric adjustment algorithms should be optimized to scale up surface reflectance from different sensors using physical and/or AI methods. These data fusion algorithms will be provided to enable the synergistic exploitation of IoT and EA time series based on Bayesian multi-sensors fusion and interpolation methods.

In PHENET, the European Research Infrastructures (RI) on plant phenotyping (EMPHASIS), ecosystems experimentation (AnaEE), long-term observation (eLTER) and data management and bioinformatics (ELIXIR) join their forces to co-develop new tools and methods for the identification of future-proofed combinations of species, genotypes and management practices in front of the most likely climatic scenarios across Europe.

YOUR MISSIONS

• Conduct a state-of-the-art review of data fusion methods applied to satellite/UAV/IoT data
• Develop and test fusion methodologies considering pro and cons of each type of observations (spatial and temporal resolution, geolocation precision, spectral information, radiometric quality…)
• Leverage cloud infrastructure and data access
• Conduct an objective comparative study between identified approaches
• Analyze performance and present results
• Collaborate with our Phenet academic partners (UCL, INRAe)
• Interact daily with an international, multidisciplinary team

EDUCATION, KNOWLEDGE AND SKILLS

• PhD in Geospatial Science, Remote Sensing, Data Science, Computer Science, or a related field.
• Autonomous and creative
• Strong proficiency in Python and geospatial libraries such as GDAL, Rasterio, GeoPandas, and xarray
• Experience with remote sensing techniques and platforms / sensors (e.g., Sentinel, Landsat)
• Knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and statistical modeling
• Familiarity with cloud computing environments (AWS, Google Cloud, or Azure) and big data processing
• Strong communication skills and ability to work in an international, cross-functional team.
• Fluent in English (oral and written): meetings with partners and internal are mostly in English.

Additionnal  "good to have"

• Background in agriculture, agronomy, or environmental science.
• Knowledge of deep learning techniques for geospatial applications.
• Familiarity with Agile development methodologies.
• Proficiency in database management for geospatial datasets.

CONDITIONS

Full-time job from May 2026 (12-15 months)
Location: Based in Balma (Toulouse, France).  Two days of work from home possible.
Mutuelle and lunch vouchers.