Postdoc: Land Data Assimilation for Climate Risk

METEO FRANCE; Toulouse; Hybride; EUR 42 000 - 56 000; Plein temps

Avantages offerts par ce poste

Flexible working hours

Telecommuting

Health insurance

Public transport subsidy

Résumé du poste

Météo-France invites applications for a fixed-term Postdoctoral Fellow position in the IRICLIM project. The role focuses on implementing LDAS, leveraging deep learning and data assimilation tools to improve drought and wildfire risk assessment.

You will work on soil moisture, vegetation, and land-surface predictors using Python in a Linux environment, and collaborate across multidisciplinary teams. The appointment is 12 months with remote work 1–2 days per week.

Qualifications

• You must hold a Ph.D. and be proficient in at least two of: deep learning, data assimilation, Earth surface modeling, and remote sensing.
• Experience programming in Python for data analysis and working in a Linux environment.
• Fluent in French.

Responsabilités

• Implement LDAS over mainland France and Corsica using atmospheric forcing from the AROME NWP model.
• Contribute to management of cross-cutting activities to implement a multi-risk approach.
• Develop and refine data assimilation approaches and risk mapping for climate-related hazards.

Connaissances

Python

French fluency

Deep learning

Data analysis

Formation

Ph.D. in a relevant field

Outils

Linux

Description du poste

Météo-France invites applications for a fixed-term Postdoctoral Fellow position in the IRICLIM project. The role focuses on implementing LDAS, leveraging deep learning and data assimilation tools to improve drought and wildfire risk assessment.

You will work on soil moisture, vegetation, and land-surface predictors using Python in a Linux environment, and collaborate across multidisciplinary teams. The appointment is 12 months with remote work 1–2 days per week.