Post-Doctoral Research Visit F/M Multi-modal Co-Learning for sensor-specific FMs

Contexte et atouts du poste

This post-doctoral position is part of the EARTH-FM project (Enhancing Archival Remote sensing data for Training Holistic Foundation Models), a joint INRIA-CNES challenge aimed at advancing the state of the art in multi-modal remote sensing Foundation Models. The project exploits large multi-temporal and multi-scale remote sensing image archives collected by CNES, such as Spot World Heritage and Pléiades World Heritage, while also exploring methodologies for data acquired through upcoming Earth Observation missions (e.g. CO3D). The work addresses challenges specific to remote sensing data, including high diversity in acquisition conditions and the integration of new modalities.

The recruited fellow will join the

Mission confiée

The objective of this position is to combine self-supervised learning and multi-modal co-learning paradigms to enhance the performance of sensor-specific foundation models....