Doktorandenstelle (65 %)Kombination von Feldbeobachtungen mit Fernerkundungsdaten in der Pflanzenphänologieforschung

The Friedrich Schiller University Jena is a dynamic and innovation-driven university centrally located in Germany. With a broad range of disciplines, it shapes the future through excellent research and teaching. Its scientific excellence is reflected in the profile areas Light – Life – Liberty, which provide pioneering insights and sustainable solutions for the society of tomorrow. Through close collaborations with leading research institutions, innovative companies, and renowned cultural organizations, it advances interdisciplinary developments. With around 17,000 students and approximately 10,000 employees, it defines Jena as a vibrant, internationally connected city of science and innovation.

Originating in the ELLIS Unit Jena, the research project “AI Generalizability in Non-stationary Environmental Regimes : The Case of Hydro-climatic Extremes (GENAI-X)”, funded by the Carl-Zeiss-Stiftung, addresses a fundamental AI challenge : achieving robust model generalizability in non-stationary environmental systems. Focusing on hydro-climatic extremes and their impacts, a multi-disciplinary team from Friedrich Schiller University Jena, the Max Planck Institute for Biogeochemistry, the Jena University Hospital, and the Senckenberg Institute for Plant Form and Function (SIP) Jena jointly develops AI models that function reliably under constantly changing conditions.

Within the framework of the GENAI-X project D3 PHENOLOGICAL SHIFT : Impacts of Extreme Events on Phenological Shifts and Ecosystem Functioning, the Plant Biodiversity Group of the Institute of Biodiversity, Ecology and Evolution, Faculty of Biological Sciences, FSU Jena, seeks to fill a

PhD Position (65%)

Combining field observations with remote sensing data

in plant phenology research

commencing on 01 April 2026. We offer a fixed-term position until 31 March 2030.

With this project we aim to harness the fast-growing phenology data from various sources, such as field observations, in-situ intervention experiments, and remote sensing, to curate a comprehensive data collection for causal modeling and as a basis for integration in climate models. The focus will be on data fusion, curation and in-depth analyses of a versatile multi-stream data source, including detailed species-level data for phenology-trait-environment relationships from elevational studies, experimental settings, semi-natural grasslands, phenological networks, PhenoCams, remote-sensing estimates, and meteorological features. This multi-scale, multi-species data source supports causal modeling of phenology representations across different plant species and communities.

Your responsibilities :

• Apply remote-sensing techniques, including terrestrial laser scanning techniques
• Merge and curate phenological data from ground-based observations from individual plants and plant communities
• Collect field data on plant phenology to complement existing data sets
• Collect plant trait information including frost-resistance measurements in the lab
• Apply advanced statistics and AI methods to analyse phenological data from different data streams and across different spatial (and temporal) scales
• Supervise student research assistants and thesis students supporting your field and computational research
• Contribute to sharing your knowledge through publications, conference presentations, outreach activities and contributions to teaching
• Work towards the completion of a PhD based in the project’s research area

Your profile :

Are you hesitating because you don't meet one or some of our requirements? Please do not hesitate to apply and give us a chance to get to know you.

We offer :

The position is offered as a fixed-term position for a maximum of four years. This is a part-time position with 65% (26 hours per week) of the working hours of a full-time employee.

Candidates with severe disabilities will be given preference in the case of equal qualifications and suitability.