PostDoc in Machine Learning and Urban Water Scarcity modelling 80 - 100% (f/m/d)

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

Swiss Federal Institute for Forest, Snow and Landscape Research WSL

Organisation/Company Swiss Federal Institute for Forest, Snow and Landscape Research WSL Research Field Computer science » Other Environmental science » Earth science Environmental science » Water science Sociology » Urban sociology Researcher Profile Recognised Researcher (R2) Application Deadline 25 Jan 2027 - 22:59 (UTC) Country Switzerland Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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.

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

PostDoc in Machine Learning and Urban Water Scarcity modelling 80 - 100% (f/m/d)

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.

Number of offers available 1 Company/Institute Swiss Federal Institute for Forest, Snow and Landscape Research WSL Country Switzerland City Birmensdorf Postal Code 8903 Street Zürcherstrasse 111