The UFZ
The Helmholtz Centre for Environmental Research (UFZ) with its 1,100 employees has gained an excellent reputation as an international competence centre for environmental sciences. We are part of the largest scientific organisation in Germany, the Helmholtz association. Our mission: Our research seeks to find a balance between social development and the long-term protection of our natural resources.
Your tasks
- Develop methodologies/tools to assess the potential impact of blue-green infrastructures for sustainable water management in urban and peri-urban environments.
- Assessment of hydrological (water balance) and hydraulic implications of blue green infrastructure on different (spatial) scales (block to city level).
- Develop methodologies for efficient sewer network planning in underdeveloped regions.
- Accquisition of project funding
- Publication of scientific results in international peer reviewed journals
We offer
- Excellent technical facilities which are without parallel
- The freedom you need to bridge the difficult gap between basic research and close to being ready for application
- Work in inter-disciplinary, multinational teams and excellent links with national and international research networks
- A vibrant region with a high quality of life and a wide cultural offering for a balance between family and professional life
- Interesting career opportunities and an extensive range of training and further education courses
- Remuneration up to the TVöD public-sector pay grade 13 including public-sector social security benefits
Your profile
- Completed university studies, doctorate and professional or research experience in the fields of hydroinformatics, urban water management, (eco-)hydrology, or comparable.
- Strong programming skills for data analysis and modeling in R or Python.
- Experience with spatial data (e.g. ArcGIS/ QGIS, vector/ raster data)
- Preferrably (but not necessarily) familiar with the following:
- Discrete Optimization
- Spatial optimization algorithms in the context of spatial networks (Clustering, Minimal Spanning Trees/Forests)
- Geospatial Python stack (geopandas, shapely, networkX)
- Basics of algorithm design/complexity analysis
- Good communication skills in English (written/ oral)
