The Center for Climate Systems Modeling (C2SM) at ETH Zurich, in partnership with the Federal Office of Meteorology and Climatology (MeteoSwiss), is pioneering innovative methods to leverage machine learning for numerical weather forecasting and climate modeling.
We are looking for a motivated Machine Learning Scientist to join the
WeatherGenerator project. Like the approach of Large Language models, the aim of the WeatherGenerator is to build a so-called foundation model for Weather and Climate. The model will be trained on various model data as well as many observations, from satellite to radar data. The core model will be then fine tuned for specific applications, such as high-resolution prediction over Switzerland.
Job description - Further develop and train the WeatherGenerator model for specific applications in Switzerland, such as high-resolution regional weather predictions
- Improve the system by integrating observation and high-resolution model data
- Fine tune and validate model against existing numerical model and observations
- Curate and validate ML training datasets
- Work on integrating the machine learning pipeline into production
The position is limited to two years.
Profile - University degree (MSc or PhD) in data science, computer science, physics or a related field
- Experience in training and validating large-scale deep-learning models on distributed systems.
- Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask)
- Experience in handling and processing large datasets or experience in high-performance computing (HPC) is an advantage
- Experience with weather and climate applications is an advantage
- You are creative, solution-oriented and have excellent communication skills and the ability to work with interdisciplinary teams
- Good knowledge of spoken and written English
We offer - Unique opportunities to develop state-of-the-art Machine Learning system and shape the future of weather forecasting
- You will join a dynamic team operating at the intersection of cutting-edge research and real-world applications
- We are committed to fostering a diverse and inclusive workplace and offer flexible working arrangements to support work-life balance for all team members
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