Job reference: VN24-05
Salary and Grade: Grade A2 GBP 71,451 (Reading/UK) or EUR 86,824 (Bonn/Germany) NET annual basic salary + other benefits
Deadline for applications: 11/02/2024
Department: Forecast
Location: Reading, UK or Bonn, Germany
Contract type: STF-PS
Publication date: 11/01/2024
Contract Duration: 2 years up to 31 May 2026, with possibility of extensions

Your role 

ECMWF has a new opportunity for a highly motivated Scientist (A2) to join us to support the development of forecast products for communicating uncertainty to users.

In this role you will develop a first set of innovative core products based on the outputs of km-scale resolution runs of the global component of the Destination Earth (DestinE) Extremes Digital Twin. By transitioning into the Digital Twin workflow machine learning and statistical methods developed during phase 1 for uncertainty quantification, you will ensure that the products provide effective communication of uncertainty. You will ensure that the products will be displayed on the DestinE core platform, easing the discovery by DestinE users of information produced by the global component of the Extremes Digital Twin. You will ensure the quality of such products.

ECMWF is one of the three organisations entrusted to deliver DestinE, a flagship initiative of the European Commission to develop a highly accurate digital model of the Earth on a global scale. ECMWF is responsible for the global component of the Extremes Digital Twin, which is currently running routinely on EuroHPC. During phase 1, a variety of techniques have been investigated, aiming at representing uncertainty in such km-scale resolution simulations. Uncertainty quantification is essential for assessing the confidence of these simulations. Ensemble predictions provide information on confidence and are key for decision making, because they quantify the probability of possible outcomes given the uncertainty in observations and models. In the global Extremes Digital Twin, large ensembles are not affordable, so machine learning and novel statistical methods offer new levels of complex data analysis to enhance the representation of uncertainty and complement ensemble methods. Such approaches have been tested in DestinE phase 1, and thoroughly evaluated, opening the possibly of implementation.

You will join an existing team in the Forecast and Services Department of ECMWF, working on applying a variety of techniques to enhance operational products from ECMWF forecasting systems.

Externally, you will work with ECMWF’s DestinE partners, ESA and EUMETSAT, service providers, 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  www.ecmwf.int 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 with 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 would 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.

For more information on DestinE, see https://ec.europa.eu/digital-single-market/en/destination-earth-destine and https://www.ecmwf.int/en/about/what-we-do/environmental-services/destination-earth 

In this role you will: 

  • Develop global products based on outputs (raw and/or post-processed) from the global component of the Extremes Digital Twin, and communicate uncertainty quantification information in an effective and consistent way
  • Review postprocessing techniques developed in phase 1 and in phase 2 by other teams to support uncertainty quantification for the Extremes Digital Twin, and transition those in the Digital Twin workflow
  • Ensure the impact of developed products from a user perspective, and propose evolution if necessary
  • Interact with relevant teams within ECMWF (and externally), especially those involved in the development of graphical interface on the DestinE core platform
  • Run evaluation/verification of such products and information, and providing documentation thereof
  • Contribute to the development and testing of complex workflows in advanced digital technology environments on some of the largest computing and data handling infrastructures in Europe
  • Contribute to regular progress reports to the European Commission ormance, comparison with other (conventional) forecasting systems.

What we’re looking for:

  • Excellent analytical and problem-solving skills with a proactive continuous improvement approach
  • Ability to effectively and creatively collect, analyse, organize, distil and present information.
  • Initiative and ability to work collaboratively with other ECMWF staff and DestinE partners, but also ability to work independently
  • Good interpersonal and communication skills
  • 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 and in a matrix management environment
  • Interest in the use of weather/environmental forecast products in an operational context/with a user-perspective

Your education, skills and experience:

  • Advanced university degree (EQ7 level or above) or equivalent professional experience in computer science or engineering, computational science, physics or natural sciences, mathematics, or a related discipline.
  • Demonstrated experience with product development from weather or climate forecasts, including post-processing and the calibration of ensemble forecasts, and representation of uncertainties.
  • Experience in the use of machine learning and statistical methods in applications within Earth system science would be an advantage.
  • Experience with developing and maintaining large scientific codes in a team would be 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) would be 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 www.ecmwf.int/en/about/jobs.

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, 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.