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 Land Change Science research unit studies patterns and processes of land systems and their dynamics over various spatial and temporal scales. As part of the Eawag-WSL collaboration in novel Biodiversity Monitoring (BiMo Initiative) the remote sensing research groups at Eawag & WSL is offering a 2-year position as a

A key component of an effective biodiversity strategy is rapid and scalable monitoring. Eawag and WSL have extensive expertise and experience in novel biodiversity monitoring approaches. The new Biodiversity Monitoring initiative (BiMo) aims to strengthen this research portfolio and generate effective practice implementation. BiMo has a strong focus on method development and outputs with high relevance for stakeholders. In addition to the remote sensing project for which we are recruiting here, BiMo comprises two further projects that will obtain information from eDNA and image analysis, with the joint objective to strengthen capacities at Eawag and WSL for developing and implementing biodiversity monitoring methods. In this project, you will examine the potential and applicability of remote sensing technologies and data (2D, 3D, active and passive sensors on different platforms) to assess and monitor terrestrial and aquatic biodiversity. You will adapt existing methods and available data on national scale to swiftly enhance ongoing monitoring programmes, identify gaps and unsolved issues and design new avenues. You will be actively involved in a large BiMo joint research proposal aimed at third-party funding.

You hold a PhD degree in environmental science, remote sensing, computer vision or an equivalent field and have sound ecological knowledge of biodiversity. You work comfortably with statistical computing and scripting languages (e.g. R, Python). You are highly motivated to analyse data using sophisticated methods and tools. Good communication and organisation skills, an excellent team spirit and fluency in German or English with very good knowledge of the other language are mandatory.