Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
in R or Python Desired - evidence of strong computational skills and large dataset analysis - experience with hierarchical Bayesian modeling - expert knowledge of plant functional ecology - fluency in
-
, the environment and ecology, transportation, robotics, energy, culture, and artificial intelligence. Overview of the CNRS as an employer: https://www.cnrs.fr/fr/le-cnrs Presentation of IRISA as the host laboratory
-
of the microbial ecology results in mineralized environment in the petrology and thermodynamic modeling components of the project. This project involves 6 (teachers)-researchers and research engineers from
-
, visit https://www.biocean5d.org/ . The applicants will work on close collaboration with Jose M. Montoya, from CNRS. - Developing analytical theory and/or simulation models on the relative importance
-
Post-doctoral position (M/F) for testing drought-based BEF relationships at CEFE Montpellier, France
ecology and ecophysiology. Experience in tree physiology and climate change impacts is a plus. • Strong background in ecological modelling, programming and analytical skills in R and strongly recommended in
-
develops innovative solutions to address the challenges of the bioeconomy and ecological transition. Global plastic production has reached unprecedented levels, yet only about 9% is recycled, with the rest
-
with a PhD in climate sciences, agronomy, biogeochemistry, or functional ecology, with a strong interest in modeling. Skills in model-data comparison and relational databases would be appreciated, and
-
of biodiversity - Knowledge of polar environments - Mastery of data acquisition and management tools in ecology or anthropology - Ability to work in a team Website for additional job details https://emploi.cnrs.fr
-
presence on forest regeneration and plant diversity 5) Influence of the environmental context (habitat, predation, hunting) on the ungulate-environment system (ecological change indicators) and implications
-
macro- scales at IJL, and to train machine learning models to predict the microstructure evolution at larger scales and longer times at SIMAP lab and Laboratoire Analyse et Modélisation pour la Biologie