Postdoc in Radar-Based Quantitative Precipitation Estimation within project EuRadCA

We are looking for a highly motivated postdoctoral researcher to join the EuRadCA project, a German-Dutch collaboration focused on advancing radar-based quantitative precipitation estimation across Europe. This position offers a unique opportunity to work at the interface of radar hydrometeorology, geospatial analysis, and machine learning, leveraging large-scale European radar datasets such as OPERA.

Job description

Key responsibilities

1. Radar data processing and QPE development

• Develop a reproducible and scalable radar processing pipeline for continental-scale radar-gauge datasets of heterogeneous quality, in close collaboration with researchers at the Royal Netherlands Meteorological Institute (KNMI).
• Implement automatic quality control (QC) on radar and gauge data, including data from official networks and personal weather stations.
• Design novel radar-gauge merging and adjustment techniques that leverage multiple radar and gauge quality indicators.
• Contribute to the development of probabilistic QPE products and uncertainty quantification.

2. Evaluation of rainfall extremes

• Assess the performance of existing and new European radar products during extreme rain.

3. Collaboration and coordination

• Work closely with PhD researchers at partner institutions in Germany (KIT, University of Stuttgart) as well as the Dutch and German national weather agencies (KNMI, DWD).
• Attend team meetings and coordinate efforts to support the creation and dissemination of the final QPE products at European scale.
• Publish results in leading scientific journals and present at international conferences.

Job requirements

We are looking for a candidate with:

• A PhD in hydrology, meteorology, environmental engineering, geosciences or a related field.
• Strong experience in weather radar, remote sensing of precipitation or spatial data analysis (e.g., geostatistics).
• Solid programming skills (e.g., Python, R or C).
• Experience working with large datasets.
• Familiarity with machine learning / deep learning is a plus.
• Experience in HPC is a plus.
• Experience in reproducible research practices and collaborative coding is a plus.
• Strong analytical thinking and ability to work independently.
• Excellent communication skills in English (oral and written).

TU Delft (Delft University of Technology)

TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society.

Faculty of Civil Engineering and Geosciences

The Faculty of Civil Engineering and Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Its research covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Research projects are conducted in close cooperation with a wide range of research institutions.

CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice.