The Senckenberg Society for Nature Research invites applications for a Postdoctoral Position in Vegetation and Ecosystem Modelling at the Senckenberg Biodiversity and Climate Research Centre (SBiK-F) in Frankfurt am Main, Germany. The position is part of the ERC Synergy project AFRI-CAN (East African Mountain Social-Ecological Dynamics) and is offered on a 3+3 year basis.
AFRI-CAN Project & Hydrological Modeling Context
Mountain ecosystems function as critical watersheds, regulating downstream hydrology, stream runoff, and water resources for human societies and aquatic biodiversity. The AFRI-CAN project aims to reconstruct and predict social-ecological dynamics in East African mountain watersheds over the past 6,000 years. The postdoctoral researcher will focus on dynamic global vegetation modeling (DGVM) and watershed hydrology, utilizing the LPJ-GUESS model to simulate ecosystem dynamics, carbon storage, and water regulation services under varying climate and land-use scenarios. Key research focus areas include:
- Adapting, parameterizing, and validating the LPJ-GUESS Dynamic Global Vegetation Model for high-altitude mountain ecosystems.
- Integrating paleoecological data (pollen, charcoal, climate proxies) to reconstruct long-term vegetation resilience and water cycle stability.
- Quantifying indicators related to biodiversity, carbon sequestration, and water regulation services in mountain catchments.
Key Responsibilities
- Develop, calibrate, and execute simulations using the LPJ-GUESS model code.
- Collaborate with an interdisciplinary team of archaeologists, ecologists, geographers, and social scientists across the AFRI-CAN consortium.
- Publish scientific articles in leading international peer-reviewed journals and present findings at global conferences.
Stipend and Benefits
- A postdoctoral contract for 3 years, with a potential extension of another 3 years (up to 6 years total).
- Competitive salary paid according to the German public sector collective agreement (TV-H E13 scale), including health insurance, pension contributions, and annual special payments.
- Access to advanced computational clusters, research facilities, and a global scientific network.
Preferred Qualifications
- Ph.D. in Ecology, Geography, Environmental Science, Hydrology, Environmental Physics, or related disciplines.
- Strong quantitative, data analysis, and programming skills (experience in C or C++ is highly desirable).
- Familiarity with dynamic global vegetation models or ecosystem process models.
- Excellent communication skills and fluency in written and spoken English.
How to Apply
Applications must be submitted online via the Senckenberg recruitment portal (quoting Reference #11-26012) before the application deadline of 15 May 2026. Please upload a single PDF containing your cover letter, CV, publication list, and contact details for two references.