Team Leader - Subseasonal Team

We are seeking a Team Leader for Sub-Seasonal Forecasting , to lead the ongoing scientific development of sub-seasonal forecasting at ECMWF within the Research Department.

ECMWF delivers operational forecasts to its stakeholders on a range of timescales from the medium‑range up to multiple seasons and beyond. Operational delivery includes world‑leading numerical sub‑seasonal forecasts, produced using a configuration of ECMWF’s Earth System model together with carefully prepared ensemble initial conditions.

The role involves leading a small team of scientists working to improve understanding of earth‑system sub‑seasonal forecast performance, processes, and predictability, and to drive improvements in ECMWF forecast performance. The team works in close collaboration with teams across ECMWF.

Responsibilities

• Lead and manage a talented team of scientists, driving the ongoing development and improvement of ECMWF’s sub‑seasonal forecasting systems, including both physics‑based and machine‑learning‑based models.
• Contribute scientific expertise to the development and assessment of ECMWF forecasts at sub‑seasonal and across timescales.
• Ensure the scientific integrity of ECMWF’s sub‑seasonal forecasting systems, and that forecast system developments meet the needs of users and applications.
• Represent ECMWF’s sub‑seasonal forecasting both internally and in international scientific and operational communities.
• Seek and secure external funding to support targeted research needs.

Qualifications

Education

• An excellent university degree and a PhD (EQF Level 8) in climate science, mathematics, physics or a related field.
• A substantial number of years’ experience in relevant scientific research.
• An appropriate record of scientific publications.

Experience, Knowledge and Skills

• Scientific excellence with a strong track record in research relevant to atmospheric and Earth system sciences.
• Experience in operational forecasting research, including understanding how scientific advances translate into forecast improvements.
• Domain expertise in sub‑seasonal prediction, including both physics‑based and emerging machine‑learning approaches.
• Proven team leadership skills, with the ability to manage, motivate, and develop a group of scientists.
• Expert knowledge of atmospheric dynamics and physical climate processes relevant to sub‑seasonal timescales.
• Extensive experience in designing, running, and evaluating forecast experiments, including the application of appropriate statistical methods.
• Proven capability to operate and work with physics‑based forecasting models in a research or operational context.
• Familiarity with machine‑learning‑based weather forecasting, with experience using ML forecasting systems considered an advantage.
• Strong programming and scripting skills, enabling efficient development and analysis of forecasting experiments.
• Demonstrated project management experience, including planning, coordinating, and delivering research activities.
• Excellent communication skills, including the ability to convey complex scientific concepts to diverse audiences.

Candidates must be able to work effectively in English and interviews will be conducted in English. A good knowledge of one of the Centre’s other working languages (French or German) is an advantage.

Location

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

Remuneration

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. Full details of salary scales and allowances are available on the ECMWF website at .

Equal Opportunity

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.