WSL – Swiss Federal Institute for Forest, Snow and Landscape Research 
Birmensdorf, Switzerland Résumé de l'offre
WSL – Swiss Federal Institute for Forest, Snow and Landscape Research seeks a PostDoc in Machine Learning and Urban Water Scarcity modelling. Based in Birmensdorf, Switzerland, this two-year position supports the NOVA-City research program, specifically the WaterScarCity project aiming to forecast water scarcity challenges for Swiss cities under changing climatic conditions. The role requires a doctoral degree in environmental sciences or data sciences, with strong expertise in machine learning methods such as LSTM and Graph Neural Networks. Candidates must possess experience in hydrometeorological modelling, programming proficiency in R and Python, and knowledge of probabilistic forecasts. Responsibilities include developing sub-seasonal forecasts and collaborating with interdisciplinary teams at WSL, ETH, EMPA, and EAWAG. Applications are due by November 15, 2026.
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Description du projet
The Swiss Federal Institute for Forest, Snow and Landscape Research WSL is part of the ETH Domain. Approximately 600 people work on the sustainable use and protection of the environment and on the handling of natural hazards.
PostDoc in Machine Learning and Urban Water Scarcity modelling 80 - 100% (f/m/d)
The WSL has initiated the Research Program “NOVA-City: Nature-based and Open Solutions for Viable, Adaptive Cities” (2027-2028) with the focus on three medium-sized cities in Switzerland and how to ensure long-term resilience, environmental sustainability, and a high quality of life under changing climatic, ecological, and societal conditions. The objective of the Nova-City project WaterScarCity (Water Scarcity Forecasting for Swiss Cities) is to help cities prepare against the challenges imposed by more frequent and intense heat and drought conditions using probabilistic subseasonal forecasts. It is located at the Research Unit Mountain Hydrology and Mass Movements, which develops novel operational hydrological forecast systems.
We are looking for the duration of two years, starting in January 2027 or by agreement, for a
You are an early career scientist with an interest in multidisciplinary research and excellent knowledge in Machine Learning methods like LSTM and Graph Neural Networks. You are expected to have a background in the use and application of weather and climate model output, with strong expertise and experience in programming (R, Python) and in the application of statistical and probabilistic forecasts. You will work on the interface of the various models developed at WSL, ETH, EMPA and EAWAG with sub-seasonal forecasts. Experience with the development of user-friendly Web-based applications in consultation with end-users and stakeholders is a plus. You publish your outcomes in scientific journals.
You have a doctoral degree in environmental sciences or related discipline including data sciences. You have experience in hydrometeorological and spatial temporal (urban) modelling and in-depth knowledge of applied data sciences and processing of Big Data. The ability to work independently, conceptually and precisely as well as flexibility and willingness to perform are among your strengths, as well as good communication skills and cooperation in an international and dynamic research team. You are fluent in English and have according to your career stage an above average publication record.
Please send your complete application to Beatrice Lamprecht, Human Resources WSL, by 15. November 2026 at the latest, by uploading the requested documents (motivation letter, CV, Doctoral Certificate, 2 references contacts) via our website. Applications via email will not be considered. Dr. K. Bogner (konrad.bogner@wsl.ch) will be happy to answer any questions or offer further information. The WSL strives to increase the proportion of women in its employment, which is why qualified women are particularly called upon to apply for this position.
Zürcherstrasse 111, CH-8903 Birmensdorf
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