Early Career Fellow - Generative Machine Learning (ML)

The DWD awards fellowships to early career scientists to work on a research project during a guest stay at ECMWF. Fellows will be based at the ECMWF offices in Bonn, Germany for a duration of two years.

The Early Career Fellow will work with scientists from different teams within ECMWF. The work will also include support by and collaboration with the Centre for Earth System Observation and Computational Analysis (University of Bonn, University of Cologne and Forschungszentrum Julich). 

In addition to the research activities at ECMWF, an important component of the STEP UP! Fellowship program is a training program offered by DWD to support the Early Career Fellows’ professional and career development during their stay with ECMWF.

The role

This position is located in the Innovation Platform of the Forecast and Services Department of ECMWF. The Fellow will work with experienced scientists and experts across different teams at ECMWF, especially those working across the organisation on the AIFS, an activity engaging experts from various fields at ECMWF.

Generative Machine learning, for example diffusion modelling, is impacting many sectors, now including weather forecasting. ECMWF has recently started running an ensemble AIFS using diffusion modelling approach. The field of generative modelling is fact moving with many developments across many disciplines. The purpose of this position will be to explore, implement and test cutting edge generative machine learning techniques in the field of weather forecasting. The successful candidate will collaborate with AIFS colleagues in these activities.

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 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 adopted a hybrid work model that is widely used by staff across ECMWF - allowing everyone to work in the office working as well as remotely up to 10 days/month, including away from the duty station. 
  
ECMWF has also developed a strong partnership with the European Union and has been entrusted with the implementation and operation of the Climate Change and Atmosphere Monitoring Services of the EU Copernicus Programme. We also contribute to the Copernicus Emergency Management Service. 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. 
See for more info about what we do. 

Main Duties and Responsibilities 

• Assessing the literature to find the most promising generative approaches
• Implementing techniques in the AIFS codebase and train models
• Thorough testing of the generative techniques in making weather forecasts 

What we're looking for

Education 

• Successfully completed scientific or technical university degree (Bachelor, Master, Diploma), preferably in physics, mathematics, computer science or machine learning, environmental sciences, hydrology, oceanography and meteorology
• Confident knowledge of written and spoken English (at least level B2 CEFR)

Experience, Knowledge and Skills

• Experience is required in training generative machine learning models applied to images/videos or similar application 
• Experience developing generative models is advantageous
• Strong Python skills (or similar language) is required
• Knowledge of written and spoken German (Level A2 CEFR)
• Experience in cooperation with international organizations is an advantage
• Very strong communication and information skills to create a sustainable positive and trusting climate of discussion when dealing with people
• Initiative and ability for constructive and collegial cooperation
• Ability to work independently and on one's own initiative to solve problems appropriately within one's own field of activity
• Ability to think and judge in order to weigh up different familiar factors and form an appropriate judgment from them
• Empathy in order to recognize different needs of participants and to be able to take them into account appropriately when dealing with groups
• Planning and organizational skills with the capacity to work on a diverse range of tasks to tight deadlines
• Intercultural competence as a prerequisite for successful cooperation in international teams and organizations

What we offer

The fellowship will amount to a monthly funding of 2,900 Euro for two years and individual expenses for travel and costs for publications in accordance with the funding principles. Further information on the possibilities of extending the fellowship (promotion) and on the program procedure can be found here:

The application period ends on September 1, 2024. The assignment will start in January 202

Who can apply

We value diversity and welcome all applications - regardless of age, gender or gender identity, nationality, ethnicity and culture, religion/belief, disability or sexual orientation.

Applications are invited from nationals from ECMWF Member States and Co-operating States, as well as from all EU Member States. 

ECMWF Member and Co-operating States are (as of July 2022): Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, Norway, North Macedonia, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Türkiye and the United Kingdom.

There is no legal entitlement to the fellowship.

The basis for the fellowship awarding are the funding principles for the STEP UP! Fellowship programs, which are also part of the fellowship contract.

How to apply

Please apply by September 1, 2024. Applications are managed outside ECMWF at the German EBV: 

For further information, please check the DWD programme website