Phd Student in Process Modelling of Biome Dynamics - Birmensdorf, Schweiz - Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft WSL

Eidgenössische Forschungsanstalt für Wald, Schnee und Landschaft WSL

Geprüftes Unternehmen

Birmensdorf, Schweiz

vor 2 Wochen

Geschrieben von:

Lena Schneider

beBee Recruiter

Beschreibung

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 process modelling of biome dynamics and evolution 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 develop model-based analyses of spatial biome dynamics through deep time by using (and adapting) the process-based biome model BIOME4 in combination with global climate reconstructions.

Using reconstructions of past biome distributions, you will assess to what degree the spatial configuration and area of past biomes has driven current patterns of biome-specific biodiversity and abiotic stress tolerance.

With your simulations you will test the biome arena size - stress resistance hypothesis, one of the two major project hypotheses.

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 you will also contribute to fieldwork in four global case study regions.

You hold an MSc degree in biogeochemial process modelling, in evolutionary modelling or in a related field, and you have excellent programming skills and knowledge of plant ecology.

You have proven experience in process modelling, in the processing of large geospatial datasets, and in the use of scripting languages (e.g. Python, R). Further assets are expertise in macroecology and/or 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.