Stage - Pré-Thèse : Détection de lacs et rivières par télédétection avec quantification d'incertitudes - Spatial - Toulouse
Core
Develop and validate methods for detecting water pixels (lakes and rivers) from remote sensing data with uncertainty quantification to support water resource monitoring.
Role type
Research intern (pre-thesis) in remote sensing and data fusion
Builds
Water detection products with confidence intervals for hydrological projects
Domain
Remote sensing / Hydrology / Machine Learning
Deliverable
production ML models
Required skills
Python, PyTorch, GDAL, QGIS, machine learning, deep learning, statistics, mathematics
Preferred skills
uncertainty quantification, data fusion, scientific reporting
Technologies
Python, PyTorch, GDAL, QGIS
Responsibilities
Conduct literature review, build datasets, develop water detection indicators, design uncertainty fusion frameworks, collaborate with application stakeholders, document results
Seniority
Intern