Scientist - Land Data Assimilation

Job summary

We have an exciting opportunity for a highly motivated scientist to advance our exploitation of satellite data in ECMWF’s land data assimilation system. The role will develop the use of observations from GNSS-R (Global Navigation Satellite Systems Reflectometry) in preparation of the European Space Agency (ESA) HydroGNSS mission that will be launched in late 2025. HydroGNSS will focus on land applications and targets four hydrological variables related to Essential Climate Variables or ECVs (soil moisture, wetlands/inundation, freeze-thaw state and forest biomass). The aim of the role will be to use GNSS-R information in an optimal way to initialise soil moisture in our global land data assimilation system and to assess the impact on Numerical Weather Prediction (NWP) and potential for future climate reanalysis.

The successful candidate will work at the forefront of developing our capabilities to use GNSS reflectometry observations to analyse land surface variables in a land data assimilation system, using a combination of machine learning and physical methods. Initially, observations from existing instruments with similar characteristics will be employed to develop ways to assimilate GNSS-R information. The candidate will also develop the dataflow for GNSS-R observations in the ECMWF land data assimilation system.

The role will be based in a team dedicated to advancing the exploitation of satellite observations to constrain Earth surfaces. The position is funded by ESA as part of the GNSS-R land data assimilation (DA) study.

Your responsibilities

• Investigate the exploitation of land surface information from GNSS-R reflectometry data with a focus on soil moisture
• Develop and implement machine learning-based observation operators to represent GNSS-R data in the ECMWF land data assimilation system
• Perform and analyse land data assimilation and coupled NWP experiments to evaluate the benefit of GNSS-R data, using existing GNSS-R data
• Ensure timely delivery of relevant results to the European Space Agency
• Communicate and document scientific results and software developments in technical reports, journal publications, conferences and meetings as appropriate

What we're looking for

• Excellent analytical and problem-solving skills with a proactive and constructive approach
• Flexibility, with the ability to adapt to changing priorities
• Ability to work autonomously and as part of multidisciplinary and geographically distributed teams
• Excellent interpersonal and communication skills
• Highly organised with the capacity to work on a diverse range of tasks to tight deadlines

Education

• The candidate should have a PhD or equivalent proven research experience in Earth System Science, Physics, Applied Mathematics, Computer Science, or a related discipline

Experience, Knowledge and Skills

• Experience in satellite data analysis, radiative transfer or data assimilation
• Some experience with land data assimilation or the use of GNSS-R data would be an advantage
• Experience with machine learning is highly desirable, ideally for geophysical applications
• Experience with performing statistical analyses and preparing scientific figures
• Strong programming skills, ideally in Python, Fortran, and UNIX shell scripting or equivalent
• Experience with working on high-performance computing platforms in Unix/Linux-based environments would be an advantage
• Candidates must be able to work effectively in English. Knowledge of one of ECMWF’s other working languages (French or German) would be an advantage

About ECMWF

The European Centre for Medium-Range Weather Forecasts (ECMWF) is a world leader in Numerical Weather Predictions providing high-quality data for weather forecasts and environmental monitoring. As an intergovernmental organisation we collaborate internationally to serve our members and the wider community with global weather predictions, data and training activities that are critical to contribute to safe and thriving societies.

Our mission: Deliver global numerical weather predictions focusing on the medium-range and monitoring of the Earth system to and with our Member States.

Other information

Grade remuneration: The successful candidates will be recruited according to the scales of the Co-ordinated Organisations. In addition to basic salary, ECMWF also offers an attractive benefits package. To find out more about working with us and for full details of salary scales and allowances, please visit www.ecmwf.int/en/about/jobs/working-ecmwf.

Starting date: 01 July 2025

Location: Reading, UK or Bonn, Germany (Candidates are expected to relocate to the duty station)

Remote work: As a multi-site organisation, ECMWF has adopted a hybrid organisation model which 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).

Interviews by videoconference (MS Teams) are expected to take place within a month after the closing date. If you require any special accommodations in order to participate fully in our recruitment process, please let us know.

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, as well as from all EU Member States.