Postdoc: ML-Driven Urban Water Scarcity Forecasts

Laplace Expert Ltd; Birmensdorf (ZH); Remote; CHF 75.000 - 110.000; Vollzeit

Zusammenfassung

Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) in Birmensdorf seeks a two-year Postdoc in Machine Learning and Urban Water Scarcity Modelling. The role links hydrological models with subseasonal climate predictions and develops ML tools for city-scale forecasts.

The position emphasizes Python/R programming, uncertainty-aware forecasts, and collaboration with ETH-domain partners. English fluency and published research are expected for this data-intensive role.

Qualifikationen

• Experience with machine learning methods for time-series forecasting.
• Proficiency in Python or R for data analysis and modelling.
• Familiarity with graph neural networks and LSTM architectures.

Aufgaben

• Develop and validate ML models to forecast urban water scarcity.
• Integrate hydrological and climate data with subseasonal predictions.
• Publish results and contribute to interdisciplinary collaborations.

Kenntnisse

LSTM

Graph Neural Networks

Probabilistic forecasting

Python

R

Tools

Python

R

Jobbeschreibung

Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) in Birmensdorf seeks a two-year Postdoc in Machine Learning and Urban Water Scarcity Modelling. The role links hydrological models with subseasonal climate predictions and develops ML tools for city-scale forecasts.

The position emphasizes Python/R programming, uncertainty-aware forecasts, and collaboration with ETH-domain partners. English fluency and published research are expected for this data-intensive role.