[ES_JOBS_NET] POST-DOCTORAL POSITION IN ECOSYSTEM MODELING, LSCE, FRANCE

POST-DOCTORAL POSITION IN ECOSYSTEM MODELING
LSCE, Gif-sur-Yvette, 17/06/2016
The land-surface modeling group at the LSCE (www.lsce.ipsl.fr/) is
looking for a post-doctoral
researcher or engineer interested in land surface and ecosystem
modeling. The position is
available for a fixed-term period of 2.5 years with a possible
extension.
The scientific context is the quantification of CO2 and CH4 fluxes
exchanged between the
terrestrial vegetation and the atmosphere and the understanding of
the underlying processes.
Within the Copernicus Atmosphere Monitoring Service (CAMS), recently
launched by the
European Commission, the LSCE will directly contribute to the
improvement of the global
greenhouse gas monitoring and forecasting system of the European
Center for Meteorological
Weather Forecast (ECMWF). The main objective is to develop global
statistical models (such as
neural networks or model tree ensembles) for specific processes
linked to CO2/CH4 fluxes, to be
inserted in the Compound Integrated Forecasting System (C-IFS) of
ECMWF. The first component
is a statistical model to compute CH4 emissions from wetland and
permafrost areas, trained with
fluxes estimated from a process-based land surface model (such as
the ORCHIDEE model) and
forced with meteorological, topographic and productivity variables
(from C-IFS). The second
component is a statistical model to relate the Gross Primary
Production (GPP) of the land surface
model in C-IFS to newly available Solar Induced Fluorescence data
(SIF) measured from space
(such as GOSAT and GOME2 instruments). The candidate will insert in
a team of researchers
with the primary objective to help constructing these statistical
models and to valorize them in
collaboration with ECMWF researchers. He/She will also use the
global land surface model
ORCHIDEE (co-developed at LSCE), including recent developments
related to natural CH4
emissions and the simulation of canopy level vegetation
fluorescence. Specific tasks of the
position will be further adjusted following discussions between the
applicant and the principal
investigators, while taking into account the experience of the
applicant. The activities will be
located at LSCE (CEA, Orme des Merisiers, Gif/Yvette, France) on the
plateau of Saclay,
approximately 25 km south-west of Paris, with some travel to England
(ECMWF).Home institution:
Laboratoire des Sciences du Climat et de l’Environnement (LSCE,
Orme-les-Merisiers, Gif-sur-
Yvette). LSCE is a joint research unit of Commissariat à L’Energie
Atomique et des Energies
Alternatives (CEA), Centre National de la Recherche Scientifique
(CNRS) and Université de
Versailles Saint Quentin-en-Yvelines (UVSQ). LSCE employs over 320
researchers covering 30
different nationalities. Their research mission is to contribute to
a better understanding of the
interactions between human activities in the Earth System,
environment and climate dynamics at
different time scales. LSCE is a world-class institute and a
thriving nexus for climate change
research.Qualifications required:
We are seeking highly motivated candidates with a degree (Master or
PhD) in for example
mathematics, physics, engineering, computer science, meteorology or
theoretical ecology.
Candidates should have preferably expertise in statistical or
process-oriented modeling and strong
desire to develop code and integrate scientific knowledge into
numerical schemes. A broad
interest in natural sciences and more specifically in terrestrial
ecology is essential.Required content of the application:
Applications and inquiries should be sent to:
Philippe Peylin (peylin@lsce.ipsl.fr)
Frederic Chevallier (chevalier@lsce.ipsl.fr)
Applications should include (1) a curriculum vitae, (2) statement of
motivation and (3) names,
addresses, phone numbers, and email addresses of at least two
references. The position is
available from September 1st and will remain open until filled with
a review of applications and
interviews starting early July. Salary follows national directives
and is adjusted for work
experience.

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