Postdoc: Holocene Dry-Season Dynamics of Central Africa

Cnrs Inc; France; On-site; EUR 38,000 - 54,000; Full time

Job summary

CNRS, through the Laboratoire des Sciences du Climat et de l'Environnement (LSCE), seeks a postdoctoral researcher to analyze the Holocene dry-season evolution in Central Africa. You will run IPSL model simulations with vegetation and carbon-cycle modules and link results to regional hydrology and forest structure.

Based in the MERMAID team on the Paris-Saclay campus, you will collaborate with partners, publish results, and contribute to broader climate-change understanding.

Qualifications

• PhD in Climate Modeling, climate variability, or interactions between climate and biogeochemical cycles (vegetation).
• Proven ability to work effectively in a team and the capacity to operate at the interface between multiple laboratories and diverse methodological approaches.
• Strong proactive mindset, creativity, autonomy, and the ability to communicate and report on research progress effectively.
• Proficiency in climate modeling and the execution of simulations, OR expertise in the analysis of large datasets (Big Data) with the ability to work on a national HPC center.
• Proficiency in English (B2–C2) and French (A2–C2).

Responsibilities

• Analyze the evolution of the dry season and related variability over the last 6,000 years using the IPSL model.
• Collaborate with project partners and work within the MERMAID team at LSCE.
• Contribute to Work Packages 4 and 5 of the ANR DYSCATTI project and prepare high-impact publications.
• Compare simulation results with paleoclimate data and recent climate evolution; disseminate findings.

Skills

Climate modeling

Big Data analysis

Education

PhD in Climate Modeling or related

Tools

IPSL climate model

High-Performance Computing (HPC)

Job description

CNRS, through the Laboratoire des Sciences du Climat et de l'Environnement (LSCE), seeks a postdoctoral researcher to analyze the Holocene dry-season evolution in Central Africa. You will run IPSL model simulations with vegetation and carbon-cycle modules and link results to regional hydrology and forest structure.

Based in the MERMAID team on the Paris-Saclay campus, you will collaborate with partners, publish results, and contribute to broader climate-change understanding.