This involves the application and development of numerical models of soil and plants, and analysis of model predictions. The modelling will be done in combination with data from lab incubation experiments, field trials, and remote sensing, and interactions within a multidisciplinary research project (incl. visit of field experiments in Europe). The ultimate goal is to identify phosphorus management practises for grassland and tillage systems which sustain plant production while minimising greenhouse gas emissions and other negative environmental impacts.
Our research focuses on land-management solutions for carbon neutrality and reduced environmental impacts of agriculture in Europe and elsewhere. The candidate will explore how different phosphorus management practises affect soils, crop yields, and greenhouse gas fluxes.
LSCE (https: // www. lsce.ipsl.fr) is an established, world-class research laboratory, representing a collaboration between CEA, CNRS and the University Paris Saclay (ranking among the best universities worldwide), and coordinating the CLAND convergence institute (https: // cland.lsce.ipsl.fr/) which gathers multidisciplinary research teams in Ile de France to conduct research and training on and-management solutions for managing the ecological and energy transitions of the 21st century. LSCE hosts approximately 300 researchers, engineers and administrative staff including many PhD and master's students. This project will provide the employee with the opportunity to work directly on advanced methods with researchers from the LSCE and other institutions. Location: Laboratoire des Science du Climat et de l'Environnement (https: // www. lsce.ipsl.fr) located about 20 km from the heart of Paris in the new research & innovation cluster plateau de Saclay.Eligibility criteria
PhD degree in environmental sciences, agronomy, applied mathematics, computer science or equivalent Strong interest in numerical modelling and issues related to agriculture, environment, and global change Proficient in written and spoken English Knowledge of programming languages (python, R, etc), machine learning and soil phosphorus fractionation are assetsWeb site for additional job details
https: // emploi.cnrs.fr/Offres/CDD/UMR8212-DANGOL-001/Default.aspxRequired Research Experiences
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Environmental science: PhD or equivalent
Biological sciences: PhD or equivalent
Geosciences: PhD or equivalent
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