Data Science Internship 2 with CERC/SLF

Data Science Internship with external page CERC/external page SLF

Deriving drivers of streamflow droughts using data-driven analysis

Streamflow drought events are triggered by rainfall or snow deficits, and further influenced by compounding conditions like evapotranspiration and water stored in the subsurface. These hydro-meteorological drivers of streamflow droughts vary across the landscape and they result in events with different characteristics (e.g., severity and duration). A good understanding of the processes causing streamflow droughts is essential to monitor and predict them.

In this project, you will explore which combinations of processes cause streamflow droughts in catchments in Europe, through a data-driven approach. Specifically, you will apply clustering algorithms (unsupervised learning) on hydro-meteorological data for multiple catchments. You will then identify classes of drought events with similar generating processes, for different regions and event characteristics.

The project will take place in an inspiring environment at the SLF and offsite with online supervision.

Qualifications required: Bachelor’s, Master’s students at ETH Zurich; familiarity with machine learning algorithms, programming (preferably R), large datasets (ideally regarding hydro-meteorological variables).

Start date: Start date as per agreement (from March 2025 on).

Duration: 6 to 8 weeks. It is expected that you spend at least two weeks of that time in Davos.

Financials: Train travel to/from and accommodation in Davos are covered. A CHF 800 stipend from ETH Zurich will be provided.

More information and application: Please send your complete application including a short cover letter, CV, certificate & transcript of your highest degree earned compiled in one PDF to Giulia Bruno,