The research group “Landscape Ecohydrology” led by Prof Doerthe Tetzlaff in the Department of Ecohydrology & Biogeochemistry of IGB in Berlin (Friedrichshagen) is inviting applications for a Postdoc position (100%, for 2 years) starting from 01.11.2024. The position is part of the “DFG” funded project “ECCO: Ecohydrological feedbacks of tropical soil-plant-atmosphere Connectivity”.
The project is a close collaboration with the Department of Geography at the University of Costa Rica led by Prof Christian Birkel and the Northern Rivers Institute, University of Aberdeen, Scotland, led by Prof Chris Soulsby. Both will be closely involved and advise during the project.
ECCO aims to achieve a novel integrated, cross-scale understanding of the partitioning of incoming precipitation in tropical systems affected by land cover change. The successful candidate will investigate temporal dynamics and spatial variability in ecosystem evapotranspiration, soil evaporation, plant transpiration and humidity recycling, soil water distribution, catchment storage and water ages in a large tropical catchment. For the purpose of upscaling point measurements to larger spatial scales, we will couple an isotope-enabled climate model directly to a process-based ecohydrological model testing soil-plant-atmosphere feedbacks.
The Postdoc will be based at IGB Berlin, but our international research team offers the opportunity for scientific exchange, travel and research stays with the partners at the University of Costa Rica, the University of Tokyo and the University of Aberdeen.
We seek a dynamic, motivated and ambitious young scientist to join an existing interdisciplinary, international science team on Landscape Ecohydrology to couple, apply and further develop an isotope-enabled climate and ecohydrology model system in tropical landscapes. It is expected that the modelling will utilise existing data sets from research sites in Costa Rica, Central America.
The successful candidate will have experience in the application of numerical models, bias-correction of large-scale climate data, programming ideally in C and Python and should also be willing to conduct own field work, for example for model calibration and validation. Expertise in using water isotopes would be advantageous. Access to high-performance computer clusters is available to facilitate the use of “state of the art” research models.