Join Our Team: Pioneering Hydrological Forecasting with Machine Learning

Are you a forward-thinking scientist eager to revolutionize hydrological forecasting? ECMWF invites you to join our dynamic team and help shape the future of global environmental predictions through innovative machine learning (ML) approaches.

Why ECMWF?

At ECMWF, we are at the forefront of Earth-system modelling and numerical weather prediction, recognized globally for our cutting-edge research and operational excellence. As the creators of the Artificial Intelligence Forecasting System (AIFS) and first operational weather centre to publish results of our own global machine learned weather model, we are pioneering efforts to integrate ML into traditional simulation models to deliver actionable insights for climate and environmental challenges.

Your Impact

In this role, you will:

• Advance the state-of-the-art in global flood forecasting through the application of deep learning
• Design, implement, and evaluate models to predict discharge, water levels, and flood inundation maps
• Collaborate closely with the Hydrology Team and ML experts to develop innovative forecasting solutions
• Lead the integration of machine-learned hydrological components as part of a European foundation model, in close collaboration with scientists working on AI Earth System modelling
• Collaborate with the AIFS team and the ANEMOI project to adapt techniques from ECMWF’s global machine-learned weather model (AIFS) for hydrological forecasting

And hence you will:

• Innovate: Design, implement and evaluate machine-learned models and workflows to enhance global hydrological forecasting—predicting river discharge, water levels, and flood inundation with precision through the application of deep learning
• Collaborate: Work alongside world-class scientists, hydrologists, and ML experts to create solutions that address extreme hydrological events impacting millions globally
• Advance Science: Adapt techniques from ECMWF’s global machine-learned weather model (AIFS) to produce trustworthy and high-performance hydrological forecast models.
• Make a Difference: Your contributions will directly improve forecasting accuracy, empowering communities to prepare for and mitigate climate-related hydrological risks.

Who You Are

• A team player who thrives on collaboration and values shared success
• Enthusiastic for continuous learning, staying current with the latest trends, research, and developments in AI and ML
• Self-motivated, efficient, and eager to contribute to technical discussions
• Skilled at documenting and communicating scientific developments effectively

Your Background

• Advanced university degree (EQ7 level or above) in a physical, computing, mathematical, or environmental science, or equivalent professional experience.
• Expertise in at least one deep learning framework (PyTorch, Tensorflow, JAX)
• Experience in the general areas of machine learning and scientific computing
• Experience with developing and applying machine learning emulators, particularly utilizing architectures such as graph neural networks and transformers
• Experience with hydrological datasets from model outputs, satellites, or observations is an advantage
• Familiarity with physical models in hydrology or environmental predictions is an advantage but not required
• Fluency in English (knowledge of French or German is a plus)

Why This Role?

At ECMWF, you’ll work at the cutting edge of science and technology, surrounded by passionate professionals dedicated to making a real-world impact. This is your chance to contribute to innovative solutions for some of the most pressing challenges of our time, from climate resilience to disaster risk reduction.

Apply today and take the next step in your scientific career while making a tangible difference on a global scale.

About ECMWF

The European Centre for Medium-Range Weather Forecasts (ECMWF) is an intergovernmental organisation created in 1975 and is today supported by 35 Member and Co-operating States mostly in Europe. The Centre’s mission is to serve and support its Member and Co-operating States and the wider community by developing and providing world-leading global numerical weather prediction. ECMWF functions as a 24/7 research and operational centre with a focus on medium and long-range predictions and holds one of the largest meteorological archives in the world. The success of its activities relies on its scientists, strong partnerships with its Member and Co-operating States and the international community, some of the most powerful supercomputers in the world and the use of innovative technologies.

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.

During COP 27 in November 2022, the UN Secretariat General launched the ‘Early Warning for All’ initiative, with the ambition that anyone in the world is covered by an early warning system or climate service by 2027, so that they are informed on upcoming climate-related disaster and lives can be saved. ECMWF is one of the world-leading centres for global hydro-meteorological forecasting and climate services, operating the Hydrological Forecast Computational Centre of the Copernicus Emergency Management Service since 2011. Every day, we generate hydro-meteorological forecast data for thousands of points and make the information available to registered users through dedicated web applications such as the CEMS European and Global Flood Awareness Systems, or data services such as the Climate Data Store. In a process of continuous evolution and improvement, ECMWF also conducts research on how to improve its Early Warning Systems and Climate Services especially on hydrological-related hazards such as floods and droughts. This Machine Learning position is at the core of the next-generation of Early Warning Systems needed to inform and improve emergency response.

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.
For additional details, see www.ecmwf.int.

Other information

Grade remuneration The successful candidate will be recruited at the A2 grade, according to the scales of the Co-ordinated Organisations. ECMWF also offers a generous benefits package, including a flexible teleworking policy. The position is assigned to the employment category STF-PL as defined in the ECMWF Staff Regulations. Full details of salary scales and allowances available on the ECMWF website at www.ecmwf.int/en/about/jobs, including the ECMWF Staff Regulations and the terms and conditions of employment.

Starting date: As soon as possible

As a multi-site organisation, ECMWF has adopted a hybrid working model that allows flexibility to staff to mix office working and teleworking. We allow for remote work 10 days/month away from the office, including up to 80 days/year away from the duty station country (within the area of our member states and co-operating states). Successful applicants and members of their family forming part of their households will be exempt from immigration restrictions.

Interviews will take place via videoconference (MS Team). If you require any special accommodations in order to participate fully in our recruitment process, please contact us via email: [email protected]

Who can apply

Applicants are invited to complete the online application form by clicking on the apply button below.

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.

Applications are invited from nationals from ECMWF Member States and Cooperating States, listed below, as well as from all EU Member States:

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

In these exceptional times, we also welcome applications from Ukrainian nationals for this vacancy.

Applications from nationals from other countries may be considered in exceptional cases.