Postdoc in ML for Urban Water Scarcity Forecasting

Academic Positions; Schweiz; On-site; CHF 90,000 - 130,000; Full time

Job summary

The Swiss Federal Institute for Forest, Snow and Landscape Research WSL invites applications for a PostDoc in Machine Learning and Urban Water Scarcity modelling. The two-year contract starts January 2027 or by agreement, based in the Research Unit Mountain Hydrology and Mass Movements in Switzerland.

You will apply ML methods such as LSTM and Graph Neural Networks to sub-seasonal forecasts, using weather and climate model outputs, with Python and R programming.

Qualifications

• Strong knowledge of ML methods including LSTM and graph neural networks.
• Experience applying weather/climate model output and probabilistic forecasts.
• Proficient programming in Python and R; publication track record.

Responsibilities

• Collaborate at interface of models across institutions (WSL, ETH, EMPA, EAWAG).
• Develop and apply sub-seasonal probabilistic forecasts for urban water scarcity.
• Publish results in scientific journals and present to stakeholders.
• Work in an international, multidisciplinary research team.

Skills

Machine Learning methods (LSTM, GraphN

English language proficiency

Education

Doctoral degree in environmental sciences or related discipline including data sciences

Tools

Python

R

Job description

The Swiss Federal Institute for Forest, Snow and Landscape Research WSL invites applications for a PostDoc in Machine Learning and Urban Water Scarcity modelling. The two-year contract starts January 2027 or by agreement, based in the Research Unit Mountain Hydrology and Mass Movements in Switzerland.

You will apply ML methods such as LSTM and Graph Neural Networks to sub-seasonal forecasts, using weather and climate model outputs, with Python and R programming.