Postdoc in assimilation of tree-ring data in a global land surface model (M/F)

CNRS; France; Sur place; EUR 35 000 - 45 000; Plein temps

Résumé du poste

A prestigious research institution in France is seeking a postdoctoral researcher to enhance global land surface models through tree-ring data assimilation. This role is funded by the ERC as part of a project aimed at improving leaf physiology and biomass growth models. Candidates must hold a PhD in physics, mathematics, or engineering, with requisite skills in data assimilation and scientific publishing. The position is full-time and temporary for 20 months, with a possible extension depending on performance.

Qualifications

• Ability to work effectively both in a team and independently.
• Proven scientific publishing experience.
• Prior experience in data assimilation with ORCHIDEE or any other land-surface model (essential).

Responsabilités

• Contribute to improving the structure and parameterisation of a tree-ring module.
• Assemble a global tree-ring database suitable for model parameterisation.
• Assimilate global tree-ring width and stable isotopes into the ORCHIDEE model.
• Lead and contribute to scientific publications on model development.

Connaissances

Team collaboration

Scientific publishing experience

Formation

PhD in physics, mathematics, or engineering

Outils

ORCHIDEE model

Description du poste

Organisation/Company CNRS Department Laboratoire des Sciences du Climat et de l'Environnement Research Field Environmental science Biological sciences Geosciences Researcher Profile First Stage Researcher (R1) Country France Application Deadline 9 Dec 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The land surface modeling group at the Laboratoire des Sciences du Climat et de l'Environnement (LSCE) near Paris is looking for a postdoctoral researcher interested in tree-ring data assimilation to improve global land surface models. The research is part of the ERC-funded project CATES. The overall goal of the position is to improve the biology and environmental sensitivity of leaf physiology and biomass growth in the ORCHIDEE global land surface model by assimilating multiple tree-ring datasets (isotopes, width, xylogenesis), which provide unique historical constraints for modelled leaf physiology (water use efficiency), carbon sequestration and wood traits. CATES will provide for the first time a long-term constraint for the land surface modelling community as ice-cores are for global circulation models. The position is for a fixed-term period of 20 months, with a possible extension based on performance.

Responsibilities

• 1. Contribute to improving the structure and parameterisation of a stand-alone tree-ring module that fully integrates source-sink growth dynamics using an existing network of ring width, stable isotopes and xylogenesis data.
• 2. Assemble a global tree-ring database suitable for model parameterisation.
• 3. Assimilate global tree-ring width and stable isotopes in the global land surface model ORCHIDEE and perform a global simulation of coupled land-climate interactions with the IPSL Earth system model.
• 4. Lead and contribute to scientific publications on model development, parameterization and improved carbon cycle simulations.

The LSCE (www.lsce.ipsl.fr/ ) is a world-class institute on climate change research and Earth System modeling located on the plateau of Saclay near Paris. It hosts the development of the ORCHIDEE model and employs over 320 researchers from more than 30 different nationalities and many scientific disciplines. The selected candidate will be part of the MOSAIC team that group researchers working on modelling processes at the interface between the land surface and the atmosphere.

Qualifications

• 2. Ability to work effectively both in a team and independently
• 3. Proven scientific publishing experience
• 4. PhD in physics, mathematics, or engineering
• 5. Prior experience in data assimilation with ORCHIDEE or any other land-surface model (essential)

Additional comments

Applications should be submitted through the CNRS jobs portal (https://emploi.cnrs.fr/ ) including (1) a curriculum vitae, (2) short statement of motivation (1 page) and (3) names, addresses, phone numbers, and email addresses of at least two references.