Post-doctoral scientific researcher (M/F)

Job Description

Missions

Context:
The effects of climate change are especially visible in the Arctic and Antarctic, which are warming faster than the rest of the world. Glacier and ice-sheet retreat, permafrost thaw, and declining snow cover threaten ecosystems and communities that depend on water, fisheries, and other natural resources, while increasing risks from avalanches and slush floods. These changes also have global consequences: melting land ice raises sea levels, and thawing permafrost releases methane and carbon dioxide. Despite these regional and global impacts, adapting to future changes in the polar cryosphere remains challenging due to large uncertainties in climate projections. Part of this uncertainty stems from insufficient understanding and inadequate model representation of the terrestrial cryosphere and its interactions with the atmosphere and ocean. Snow strongly influences these interactions and plays a key role in modulating the cryosphere's response to climate change and other natural and socioeconomic drivers. Yet, in polar regions, snowpack characteristics and processes remain poorly understood, observed, and modeled, particularly those underlying atmosphere–terrestrial cryosphere interactions. Addressing these knowledge and modeling gaps is therefore critical to improving projections and supporting effective climate adaptation.
The SnowPI (Polar Snow, Permafrost, and Inland Ice in a Changing World) project began in 2026 to address these challenges by advancing our ability to understand, observe, study, and project changes in the frozen terrestrial surface through the lens of snow. SnowPI will leverage emerging technologies, scientific discoveries, state-of-the-art models, in-situ and remotely sensed observations, and novel observations and model developments. Uniquely, it will also pursue a novel approach to developing climate information to support adaptation strategies in the polar regions, following two converging pathways that can exploit emerging scientific and modeling advances more rapidly than traditional approaches. SnowPI will contribute: 1) new knowledge and improved capabilities to model and observe changes in snow, glaciers, ice sheets, and permafrost; and 2) state-of-the-art assessments of regional and global impacts of a changing cryosphere to support climate adaptation. Together, these results will benefit actors within and beyond the polar regions by strengthening their capacity to respond to climate change.

Overall Goal of this study:

In this postdoctoral study, the goal is to improve the representation of snowpack characteristics by developing novel parameterizations using new and existing observations. The SURFEX land surface model will be used primarily in offline mode (uncoupled to the atmosphere and driven by point-scale observations) to conduct sensitivity experiments implementing existing but untested snow process representations (e.g., blowing snow) and introducing new processes, including the impacts of depth hoar formation on snow thermal conductivity, snow albedo changes due to particulate matter or impurities, and soil state below the snow-covered patch fraction. Simulations will be conducted at local and kilometer scales over Greenland, Svalbard, and the Antarctic Peninsula, where independent in-situ observations are available for model evaluation. New developments will be tested offline using existing and SnowPI observational datasets, while collaboration with SnowPI partners will enable assessment of their impacts on regional climate using HCLIM-AROME in collaboration with project partners in Norway.

Activity

Conduct a bibliographical review of the current state of the representation of high-latitude processes in snow models used for large-scale hydrological and climate modelling applications.
-Develop new modules, functions, or routines within SURFEX to represent processes that are currently missing or inadequately represented, or that require further improvement.
-Perform model simulations and sensitivity tests at both the local and, where appropriate, regional scales.
-Write and contribute to scientific publications resulting from this project, as well as reports for the EU project.
-Present the results of this work at international conferences, meetings, and workshops.
Main objectives:
-Which snow processes are missing or poorly represented in current models for high-latitude and polar regions? What is the current state of the art?
-What level of model complexity is required to represent these processes more accurately?
-Which of these processes are most critical for representing the evolution of the snowpack under future climate conditions?

Your Profil

Skills

A PhD at the time of the start of employment in meteorology, hydro-meteorology, or a related field (with a preference given to those with experience in cold season surface process modeling). The candidate should have good programming skills for the processing of large volumes of data, and be capable of performing model evaluations using different in situ and remote-sensed datasets. Preferred programming languages are Python and FORTRAN. A good proficiency in Linux command shell is required. It is expected that the candidate has the level of English needed for writing reports and peer-reviewed publications, as well as for participating in teleconferences/conferences/project workshops. We are seeking someone who is creative, motivated, fairly independent and willing to work in collaboration with other researchers and laboratories. The working language is English and/or French.

Your Work Environment

The successful candidate will be based at the National Centre for Meteorological Research (CNRM) located on the Météo-France campus in Toulouse, France. It is a Joint Research Unit (UMR 3589, www.umr-cnrm.fr) supervised by Météo-France and the CNRS (French National Centre for Scientific Research). CNRM conducts research in the fields of meteorology and climate, ranging from the observation, understanding, and modeling of atmospheric and environmental processes to the development of weather forecasting and climate projection systems that can be transferred to Météo-France's operational services. The postdoctoral researcher will be based within the mesoscale modeling division (GMME) and, more specifically, in the SURFACE team which specializes in the development of physical parameterizations and the study of land-surface processes, particularly in the field of hydrometeorology, as well as their coupling with the atmosphere.

Constraints and risks

No particular constraints or risks.

Compensation and benefits

Compensation

The gross monthly salary will be between 4216 to 4395 euros per month commensurate with experience (2 to 10 years): this includes French social security.

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

The research professions