Machine Learning Scientist for Weather and Climate (WeatherGenerator project)

ETH Zürich
Zürich, Switzerland
17 days ago

Role details

Contract type
Temporary contract
Employment type
Part-time / full-time
Working hours
Regular working hours
Languages
English
Compensation
CHF 208K

Job location

Zürich, Switzerland

Tech stack

Big Data
Computer Programming
Distributed Systems
Machine Learning
High Performance Computing
PyTorch
Deep Learning
Information Technology
Dask

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

Requirements

  • 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

Benefits & conditions

80%-100%, Zurich, fixed-term

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., * 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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