The Swiss Federal Institute for Forest, Snow and Landscape Research WSL is a part of the ETH domain. Approximately 500 people work on the sustainable use and protection of the environment and on the handling of natural hazards.
The Research Unit Landscape Dynamics studies patterns and processes at the landscape level caused by ecological and anthropogenic drivers. Within the project „SPEEDMIND – Improving species biodiversity analyses and citizen science feedback through mining data“ we are offering a 1 year position (with a possible 1 year extension) as a
PostDoc – Quantitative Ecology / Biodiversity Modelling
You will explore the potential of data mining and machine learning techniques in order to facilitate biodiversity analyses and to foster the link between ecological and citizen sciences. Focussing on floristic data from Switzerland, you will combine species occurrences with trait and phylogenetic data as well as various environmental information to assess the effect of sampling bias and data source on spatiotemporal uncertainty patterns, fill data gaps, identify higher-level ecological processes structuring biodiversity, and guide citizen science based data collections. Your tasks will include implementing the required workflows as well as analysing and publishing the ecological results. You will closely collaborate with the WSL-team, as well as with data mining specialists from the Swiss Data Science Center (SDSC).
You have a PhD in ecology or a related field. You are highly motivated and you like to work independently and well-organized in a dynamic, international team. Furthermore, you have excellent knowledge of ecological theory and a strong interest in methodological, data oriented questions, strong quantitative skills including fluency in R, are experienced in working with cluster computers (e.g. slurm based), experienced in species distribution modelling, and in calculating diversity metrics at multiple scales. Knowledge in Python, Java, or SQL, is an advantage. You have excellent written and oral communication skills in English, and a good publication record. Knowledge of German is recommended but not mandatory.
Please send your complete application to Sabine Hirt, Human Resources WSL. Niklaus Zimmermann (firstname.lastname@example.org) will be happy to answer any questions or offer further information. The WSL strives to increase the pro-portion of women in its employment, which is why qualified women are particularly called upon to apply for this position.