Phd Student in Global Plant and Biome Ecology

vor 4 Wochen

Birmensdorf, Schweiz Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft WSL Vollzeit

Swiss Federal Institute for Forest, Snow and Landscape Research WSL

The Swiss Federal Institute for Forest, Snow and Landscape Research WSL is part of the ETH Domain. Approximately 600 people work on the sustainable use and protection of the environment and on the handling of natural hazards.

The research group Dynamic Macroecology of Dr. Niklaus E. Zimmermann studies questions related to spatial ecology, macroevolution and biodiversity conservation. For this group, we are looking from
**early 2024** for a

PhD Student in global plant and biome ecology 80-100% (f/m/d)

as part of a large SNSF (ERC) Advanced Grant project (Predicting hotspots of climate change impacts on ecosystems from an eco-evolutionary biome framework). This project aims at (1) mapping global biomes, (2) projecting global change impacts on biomes, and (3) testing a novel eco-evolutionary biome theory. As part of this large effort, you will assess how recent climate change has led to biome shifts and how it affected the frequency and intensity of different types of (a)biotic disturbances. You will then project the relationships identified to future climates based on projections of climate models. For this research, you will analyze large global data sets on vegetation structure, climate, and other geospatial properties, and you will carry out fieldwork collect data on disturbances that cannot easily be measured from space and to validate model projections in the field. The project will be carried out in close cooperation with international partners. The main place of work will be the Swiss Federal Research Institute WSL in Birmensdorf, Switzerland, but part of your work will be conducted in the four global case study regions.

You hold an MSc degree in plant ecology, macroecology or a related field, you are an enthusiastic field ecologist with proven experience in planning and conducting complex sampling campaigns, and you have good knowledge in processing high-volume data with code-based tools. You have proven experience in spatial modelling and in the use of scripting languages (e.g. Python, R). Further assets are expertise in functional ecology, and experience in cluster computing, machine learning, and artificial intelligence. The capability to develop new ideas independently is necessary, as are very good English skills (both written and oral). You are a curious, self-reliant person who is also an excellent team worker and values cooperation.
- Zürcherstrasse 111, CH-8903 Birmensdorf

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