Doctoral or Postdoctoral Researcher (f/m/d) - Global Vegetation and Biome Modelling

Position

Doctoral or Postdoctoral Researcher (f/m/d) - Global Vegetation and Biome Modelling

Employer

Senckenberg – Leibniz Institution for Biodiversity and Earth System Research (SGN)

Overview

Senckenberg is one of the world’s leading research institutions in the field of Biodiversity and Earth System Research, with eight research institutes across Germany and scientists from over 40 nations. Our headquarters are located in the thriving commercial metropolis of Frankfurt (Mainhattan) in the heart of Germany, which also hosts one of our most famous facilities, the Senckenberg Natural History Museum. The mission of the Senckenberg Biodiversity and Climate Research Centre is to study the complex interactions between biodiversity and climate change. The announced position is embedded in a coordinated Focus Unit Project (FUN) within the TERRA (Terrestrial Geo-Biosphere Interactions in a Changing World) excellence cluster, a collaboration between Senckenberg and the Universities of Tübingen and Hohenheim. The focus research unit brings together biologists, geologists and earth system modellers who together aim at fundamentally advancing our understanding of “The past and future of the C4 grasslands of the world”. We will develop a novel approach for simulating C4 grasslands in interaction with C3 grasslands and trees based on Eco‑Evolutionary Optimality (EEO) within the framework of the LPJ‑GUESS Dynamic Global Vegetation Model. Geologists in the team will advance the state‑of‑the‑art in reconstructing Oligocene to Miocene C3/C4 transitions, which will be used to test the new vegetation model. The new EEO‑based vegetation model should then also be used to predict future transitions and biome shifts to ultimately answer the question to what extent C4 grasslands, savannahs and their unique biodiversity will persist under future climate change.

Location

Frankfurt/Main, Germany

Sector

Academic

Divisions

• Biogeosciences (BG)
• Climate: Past, Present & Future (CL)
• Energy, Resources and the Environment (ERE)

Type

Contract

Level

Experienced

Salary

See job advertisement

Preferred Education

PhD

Application deadline

22 February 2026

Posted

10 February 2026

Responsibilities

• Further develop our implementation of the EEO‑based P model for photosynthesis within LPJ‑GUESS
• Test the model against observations of the current distribution of C4 grasslands and reconstructions of past dynamics, including the time when they first expanded across the globe
• Use the model to predict the future of C4 grasslands and savannahs using the latest CMIP6 climate projections
• Collaborate with geologists and climate modellers in the team to infer the climate conditions and CO‑2 concentrations at which C3/C4 transitions occurred in the past
• Publish results in scientific journals with highest scientific standards

Qualifications

• Master or PhD degree in Biology, Plant Ecology, Environmental Modelling, Geography, Environmental Physics or related fields
• A strong interest in plant ecology and climate change
• Strong programming skills in C++, the language of the LPJ‑GUESS code, or another fundamental programming language such as C or Fortran
• Strong expertise in data analyses and statistics
• Experience in ecological or environmental modelling
• Documented ability to publish scientific papers in international journals (for postdoctoral candidates)
• Research experience in interdisciplinary working environments is beneficial
• Excellent written and oral communication skills in English

Contact

If you have any specific questions about the position, please contact Prof. Dr. Thomas Hickler at For data protection information on the processing of personal data as part of the application and selection process, please refer to the privacy policy on our homepage at

How to apply

Please send your application (letter of motivation, CV, contact details of two references, and certificates) electronically (as a single PDF) to under the heading "Application: Your Name (FUN05_1)" and stating the reference # .