Scientist - Narrative-based diagnostics of data-driven forecasting in Destination Earth

Your role 

ECMWF has a unique new opportunity for a motivated and innovative Scientist (A2) with interest in communicating science results in the context of the rise of AI-based weather forecasts in the framework of Destination Earth (DestinE). 

At ECMWF, you will find a passionate community, collectively aiming to build the world-leading global Earth system models for numerical weather prediction. ECMWF was the first operational weather centre to publish results of their own global machine learned weather model – the Artificial Intelligence Forecasting System (AIFS) – that are continuously updated with the latest predictions on their webpage. Within DestinE, ECMWF now develops and deploys workflows of machine-learned Earth-system components of a European foundation model based on existing DestinE traditional simulation and modelling results. You  will play a key role in advancing AI-based prediction capabilities, by developing novel ways of evaluating severe weather forecasts and understanding the quality of AI-based forecasts. 

You will contribute to enhance the evaluation workflow of weather prediction systems. Your aim will be two-fold: (a) to perform in-depth evaluation of specific aspects in the AI-based forecasts, used also for uncertainty quantification in DestinE, aiming at identifying strengths and weaknesses and understanding the underlying causes; and (b) to work on the interpretation and communication to a wide audience of the outcomes of such analyses. Developing storytelling for specific case studies will be instrumental in illustrating the quality and potential of AI-based predictions, also putting into perspective comparisons with the performance of conventional prediction systems (including those used in the Extremes Digital Twin of DestinE). 

By ’telling the story’ of AI-based forecasts as part of regular forecast performance monitoring, you will help accelerate both, the progress in and the uptake of AI-based predictions from various internal and external stakeholders in a visible and an innovative way. 

You will work in collaboration with a range of colleagues across ECMWF, and in particular scientists working on Digital Twins and machine learning developments and the team developing the AI version of the Integrated Forecasting System (AIFS) of ECMWF. Externally you will work with ECMWF’s DestinE partners, ESA and EUMETSAT, service providers and ML experts in the National Meteorological and Hydrological Services of ECMWF Member States and Cooperating States as well as stakeholders and prospective users of the Digital Twins.

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. 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.

See   for more info about what we do. 

The Destination Earth (DestinE) initiative

ECMWF is one of the three entities entrusted to implement the DestinE initiative of the European Commission, alongside ESA and EUMETSAT as partners. DestinE aims to deploy several highly accurate thematic digital replicas of the Earth, called Digital Twins. The Digital Twins will help monitor and predict environmental change and human impact, in order to develop and test scenarios that support sustainable development and corresponding European policies for the Green Deal.  ECMWF is responsible for the delivery of these digital twins and of the Digital Twin engine, the software infrastructure needed to power them of some of Europe’s largest supercomputers, those of the European HPC Joint Undertaking (EuroHPC). The second phase of DestinE covers the period June 2024 – May 2026, and future phases are foreseen (subject to funding). Phase 2 will focus on early operations with consolidation, maintenance, and continuous evolution of the DestinE system components developed in the first phase. There will also be an enhanced focus on ML activities, including the deployment of workflows of components of a ML model for the Earth system, optimisation of the Digital Twin Engine to enable efficient model training and simulations, and other activities.

For more information on DestinE, see  and

In this role you will: 

• Develop and adapt diagnostics tools, including visualization, aiming at understanding strengths and weaknesses in AI-based Earth system predictions, and embed such tools in DestinE work  flows.
• Apply diagnostics to simulations run with AI-based predictions within DestinE.
• Perform systematic qualitative and quantitative comparison of data-driven and physical-based predictions, in particular in DestinE, focusing on the forecast skill of high impact weather events.
• Develop compelling narratives on the interpretation and significance of results of such comparison – augmenting the “traditional” physical understanding with insights gained from AI approaches.
• Develop “short stories” to communicate results to internal and external audiences on the quality of the AI predictions, in particular on specific case studies; illustrate progress in the development of AI-based forecasts.
• Investigate the possibility of connecting the relevant diagnostic suite to the chatbot developed in DestinE to allow for better interactivity.

What we're looking for:

• Analytical and problem-solving skills with a proactive continuous improvement approach.
• Communication skills with the ability to translate technical information into accessible and compelling narratives.
• Motivation to actively contribute to technical discussions and work with others to identify the best way to proceed. 
• Initiative and ability to work collaboratively with other ECMWF staff and DestinE partners, but also able to work independently.
• Dedication, passion and enthusiasm to succeed both individually and across teams of developers.
• Highly organised with the capacity to work on a diverse range of tasks to tight deadlines.

Your education, skills and experience:

• Advanced university degree (EQF Level 7 or above) or equivalent professional experience or professional qualification in Earth System Science, Physics, Statistics, Applied Mathematics, or a related discipline.
• Experience in working on physical processes understanding in weather or climate models and/or experience in evaluation of weather and climate predictions is required.
• Experience in science communication is required.
• Experience in handling large observational data and/or modelling datasets is an advantage.
• Very good programming and scripting skills are an advantage.
• Experience in working with physical or machine learning models in the domain of weather and climate prediction is an advantage.
• Experience in machine learning, and particularly deep learning, within the area of weather and climate science is an advantage.
• Candidates must be able to work effectively in English.
• Good knowledge of one of the Centre’s other working languages (French or German) is  an advantage.

Other information 

Grade remuneration:  The successful candidates will be recruited at the A2 grade, according to the scales of the Co-ordinated Organisations. The position is assigned to the employment category STF-PS  as defined in the ECMWF Staff Regulations. Full details of salary scales and allowances available on the ECMWF website at . 

Starting date:  As soon as possible

Candidates are expected to relocate to the duty station. As a multi-site organisation, ECMWF has adopted a hybrid organisation model which allows flexibility to staff to mix office working and teleworking, including away from the duty station (within the area of our member states and co-operating states).

Interviews by videoconference (MS Team) are expected to take place shortly after the closing date. 

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 Co-operating States: 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. 

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.