The project focuses on soil-dependent pollinators, e.g. ground-nesting bees, and their relationship to soil conditions. In collaboration with soil scientists, it will examine the extent to which land use and climatic conditions influence soil-dependent pollinators. Samples will be collected in Germany as well as European project partner countries and include sampling for chemical and physical soil properties, soil fauna, and pollinators. New methods to sample and monitor pollinators will be developed.
Tasks:
- Development and testing of new methods (e.g. eDNA, Camera and drone imagery, deep-learning based image analyses) for monitoring soil-dependent pollinators, especially ground-nesting wild bees
- Application of new methods to investigate ecological research questions within the ProPollSoil project, e.g., analyzing whether ground-nesting wild bee diversity differs across land-use categories and soil types
- scientific services in research, including authoring and publishing peer-reviewed scientific articles and presenting research findings in team meetings and at scientific conferences
Table of Content
Summary
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Benefits
- Integration into a broad research network – both at the University of Marburg and through collaboration with the 23 partners of the ProPollSoil project, especially from the LMU Munich
- Professional development opportunities
- Regular exchange with other research groups
- Ticket for free use of public transportation in the state Hesse, Germany
- German retirement plan (VBL) benefits
Requirements
- MSc degree (or equivalent) in biology, nature conservation, environmental sciences, bioinformatics or a related field
- Experience with, or a strong willingness to learn, computer-based data acquisition and analysis methods (e.g. statistics in R or Raspberry Pi programming)
- Effective team player with strong collaboration skills
- Excellent writing and presentation skills in English and sufficient proficiency in German, or a demonstrated willingness to learn, to manage everyday work in Germany
- Experience with, or a strong willingness to learn, at least one of the above-mentioned methods (eDNA, AI-based cameras, drones)
- Willingness to collaborate across disciplines, especially with bioinformatics and soil ecology
Disposition to own scientific qualification is expected.
Application Deadline
March 29, 2026How To Apply
For more information, kindly visit the University of Marburg website.
