Scholarship for PhD Studies at Max Planck Institute for Biogeochemistry

Страна: Германия;

Дедлайн: 30.11.2010


Адрес: Max Planck Institute


The research group is dedicated to a better understanding of the role of Vegetation-Soil feedbacks for biogeochemical cycles within the Earth System. In particular we are focusing on the interaction between the carbon and water cycles at different spatial and temporal scales. The integration of knowledge gained by exploring local data (e.g. ecosystem carbon and water flux data, soil profile information) and spatial data (e.g. remote sensing, spatial data bases) into process-based dynamic models will play a pivotal role in this context.

The PhD candidate will contribute to these issues from a carbon cycle modelling perspective. We are using and developing dynamic global vegetation models which combine representations of biogeochemical fluxes and terrestrial vegetation dynamics to address the response of ecosystem functions to climate change. The PhD candidate is dedicated to improve such a process-based model with respect to vegetation carbon processes by making use of remotely sensed information about the ecosystem state and function.
Requirements:Key requirements for this PhD position are scientific enthusiasm, strong abilities in quantitative, abstract and system-oriented thinking and the ambition to publish results in international peer-reviewed journals (English language), as well as advanced practical skills with respect to computer-based data analysis and scientific programming. Candidates with background (Diploma, Master, or equivalent) in any quantitative science (e.g. geo-ecology or other geo-science, environmental and natural sciences, applied mathematics or computer science) are eligible for these positions, given their strong motivation to complement their past training. Experience with at least one of the following topics is helpful: system modeling, advanced statistical data analysis, vegetation ecology, remote sensing products, forest inventory, ecosystem CO2 and energy flux data.