Scientist for Machine Learning

**The role**:
**The team**:
The position will be part of the Earth System Modelling section at ECMWF and tightly linked to the different machine learning efforts at the Centre, e.g. the AIFS, ECMWF's data-driven forecasting model and the WeatherGenerator project.

**About ECMWF**:
The European Centre for Medium-Range Weather Forecasts (ECMWF) is a world-leader in weather and environmental forecasting. As an international organisation we serve our members and the wider community with global weather predictions and data that is critical for understanding and solving the climate crisis. We function as a 24/7 research and operational centre with a focus on medium and long-range predictions, holding one of the largest meteorological data archives in the world. The success of our activities builds on the talent of our scientists and experts, strong partnerships with 35 Member and Co-operating States and the international community, some of the most powerful supercomputers in the world, and the use of innovative technologies and machine learning across our operations.

ECMWF has also developed a strong partnership with the European Union and has been entrusted with the implementation and operation of the Destination Earth Initiative and the Climate Change and Atmosphere Monitoring Services of the Copernicus Programme. Other areas of work include High Performance Computing and the development of digital tools that enable ECMWF to extend provision of data and products covering weather, climate, air quality, fire and flood prediction and monitoring.

ECMWF is a multi-site organisation, with a main office in Reading, UK, a data centre/ supercomputer in Bologna, Italy, and a large presence in Bonn, Germany. We appreciate the need for flexibility in the way our staff work. We have adopted a hybrid work model that allows flexibility to staff to mix office working and teleworking, including away from the duty station for up to 10 days/month (within the area of our member states and co-operating states).

**About the projects**:
**Main duties and key responsibilities**:
**ICON-Rep**:

- Adapt the existing AtmoRep model to support the native ICON-grid and explore the possibility to do climate scenario interpolation and extrapolation
- Support overall AtmoRep model developments, including for in the WarmWorld sister project ICON-Rep-Model at the Jülich Supercomputing Centre

**EXPECT**:

- Implement downscaling of climate data using a generative machine learning model using high-resolution model output from DestinE, EERIE, and nextGEMS
- Support coordination of EXPECT’s theme one data for new climate knowledge

**What we are looking for**:

- Dedicated and enthusiastic about teamwork but also self-motivated and able to work with mínimal supervision, taking responsibility for the project
- Excellent analytic skills to analyse problems and methodologically develop potential solutions and empirically evaluate them
- Excellent interpersonal and communication skills, and ability for efficient documentation and communication of scientific results
- Significant experience developing in Python or similar languages, and the use of software version control and best practices for software development
- Substantial experience with at least one deep learning framework (usually either PyTorch or JAX), in particular development and tuning of new architectures and training protocols
- A background in Earth system modelling is welcome but not required. Experience with large HPC systems is an asset

**Education**
- Advanced university degree (EQ7 level or above) in a computing, physical, mathematical or environmental science, or equivalent professional experience

**Experience, Knowledge and Skills**
- Experience in the general areas of machine learning and scientific computing
- Experience in machine learning and particular in machine learning model development
- Ability to deliver ready-to-use code
- Experience with generative machine learning and Earth system modelling is desirable

**Other information**:
**Starting date**: as soon as possible

Interviews will be conducted by videoconference (MS Teams).

Successful applicants and members of their family forming part of their households will be exempt from immigration restrictions.

**Who can apply**:
At ECMWF, we consider an inclusive environment as key for our success. We are dedicated to ensuring a workplace that embraces diversity and provides equal opportunities for all, without distinction as to race, gender, age, marital status, social status, disability, sexual orientation, religion, personality, ethnicity and culture. We value the benefits derived from a diverse workforce and are committed to having staff that reflect the diversity of the countries that are part of our community, in an environment that nurtures equality and inclusion.

ECMWF Member States and Co-operating States are: Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Georgia