Wissenschaftliche Mitarbeiterin/Wissenschaftlicher Mitarbeiter...
Core
Develop nationwide suitability and risk maps for grain legumes (pea, chickpea, soybean, lupin) by integrating soil, weather, and climate data with process-based plant growth models and expert knowledge.
Role type
Research scientist (agricultural systems & data science)
Builds
Publicly accessible suitability and risk maps for crop selection and climate-resilient farming systems
Domain
Agriculture, Plant Science, Geoinformatics, Data Science
Deliverable
production ML models
Required skills
Statistical analysis (multivariate methods, clustering), Programming (R, Python), GIS (QGIS, ArcGIS), Process-based plant growth modeling, Spatial data analysis, Crop physiology knowledge
Preferred skills
PhD in relevant field, Experience with decision support systems
Technologies
R, Python, QGIS, ArcGIS, Relational databases
Responsibilities
Harmonize and analyze large-scale spatial and temporal environmental data; Develop hybrid evaluation frameworks combining data-driven and rule-based approaches; Create GIS-based suitability and risk maps; Validate map products using independent trial data; Support PhD student in model calibration and simulation; Coordinate project activities and partner workshops; Publish results in scientific journals.