The WSL Institute for Snow and Avalanche Research SLF is part of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL and thus of the ETH Domain. WSL focuses on the sustainable use and protection of the environment and on the handling of natural hazards. WSL employs approximately 600 people, of whom 140 work at SLF in Davos.
The Research Unit Snow Avalanches and Prevention investigates the formation and dynamics of avalanches, develops prevention measures in the context of integral risk management, operates warning and information systems and is responsible for avalanche warning in the Swiss Alps. The group Warning and Information Systems is looking for a (f/m/d)
Data Scientist or Engineer (80-100%)
As part of a two-year project supported by the Swiss Data Science Center (SDSC), you develop and operationalize algorithms to improve the data quality of snow and weather data from the IMIS monitoring network, which is an important basis for avalanche warning and numerical models to support it. The algorithms should allow for real-time detection of anomalies in the time series, but also the detection of outliers, and impute missing data by applying state-of-the-art machine learning approaches. You will work together with SDSC scientists and software engineers at the SLF.
You have a Master's degree or a doctoral thesis and are used to developing and operating data pipelines. You are familiar with machine learning methods and time series databases. Very good knowledge of English and organizational skills are expected. Furthermore, you are team-oriented as well as proactive and bring along an independent way of working as well as joy in scientific work.
Please send your complete application to Jasmine Zollinger, Human Resources WSL/SLF, by uploading the requested documents through our webpage. Applications via email will not be considered. Prof. Dr. Jürg Schweizer, phone +41 (0)81 417 01 64, 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.