Postdoc: AI for Satellite-Derived Wet-Bulb Temperature

EURAXESS Ireland; France; Hybride; EUR 28 000 - 36 000; Plein temps

Résumé du poste

LATMOS hosts a postdoctoral researcher to compute wet-bulb temperature from satellite data using deep learning, with a focus on IASI and IASI-NG missions. The project is conducted in collaboration with INRIA, within the Atmospheres department.

The candidate will employ neural networks, co-locate satellite data with HadISD stations, and contribute to conferences and a publication, based in France.

Qualifications

• PhD in Earth/environmental sciences or remote sensing with AI applications.
• Experience with Python and Linux for data processing.
• Experience applying deep learning to satellite data and climate/atmospheric studies.

Responsabilités

• Understand infrared data from the IASI mission and identify channels for wet-bulb temperature retrieval.
• Co-locate satellite data with HadISD ground stations.
• Develop and compare neural network architectures for case studies on India.
• Present findings at conferences and prepare a peer-reviewed paper.

Connaissances

Python

Linux

Deep learning

Remote sensing

Formation

PhD in Earth/environmental sciences/remote sensing with AI applications

Outils

Python

Linux

Description du poste

LATMOS hosts a postdoctoral researcher to compute wet-bulb temperature from satellite data using deep learning, with a focus on IASI and IASI-NG missions. The project is conducted in collaboration with INRIA, within the Atmospheres department.

The candidate will employ neural networks, co-locate satellite data with HadISD stations, and contribute to conferences and a publication, based in France.