This is how you can contribute

• Implement existing or develop new solutions to derive agri-environmental information or indicators from satellite data
• Analyse Earth Observation data streams (e.g. satellite, weather, soil) with machine learning approaches
• Link remote sensing and environmental data to analyse the impact of land use on the agricultural landscape
• Publication of scientific and practice-oriented publications (in English and German), reports and maps
• (Co-)development and management of projects, and potentially acquisition of third-party funding and support and supervision students
• Contribute to developing Agroscope's Agricultural Landscape Intelligence System

This makes you unique

• A PhD degree and a Background in the fields of agricultural sciences/agronomy, plant physiology or environmental sciences
• A solution-oriented, self-motivated and self-organised approach to work and a positive attitude towards support/collaboration with colleagues
• Experience and enjoyment of developing applicable solutions and to communicate them to stakeholders, e.g. in (scientific) reports and presentations
• Strong programming skills in Python and proven, strong skills in machine learning
• Experience with spatial data and remote sensing are a benefit
• Knowledge of two official Swiss languages and spoken and written English

In a nutshell

Are you interested in contributing to a more sustainable use of our natural resources and do you have strong expertise in machine learning? Are you eager to apply state-of-the-art methods to develop and implement solutions for applied research questions-while advancing scientific knowledge at the same time? Then we look forward to receiving your application.
Please clearly indicate in your application how your profile and experience match the requirements of this position.
Applications should be submitted in English.
Interviews will start after the 01.07.2026.