Team Leader - Ensemble Modelling

ECMWF

Reading

Hybrid

GBP 80,000 - 110,000

Full time

14 days+

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Job summary

ECMWF, based in Reading, UK with operations in Bonn, Germany, seeks a Team Leader for the Ensemble Modelling Team. You will guide the scientific and managerial direction of ensemble prediction across multiple timescales, coordinating with colleagues across data assimilation, atmospheric, ocean and land modelling, and machine-learning pipelines to deliver reliable probabilistic forecasts.

You will lead a team of around a dozen scientists, shaping priorities, planning the programme, and fostering

Responsibilities

  • Lead and manage the Ensemble Modelling Team, setting objectives and priorities, supporting effective delivery, coaching and developing team members
  • Work with the Head of Earth System Modelling to shape the scientific direction for ensemble prediction across medium-range, sub‑seasonal, seasonal and longer‑range applications, leveraging physics‑based, AI‑based and hybrid approaches
  • Guide the design and further development of ECMWF’s operational ensemble prediction systems to support the delivery of world‑leading operational ensemble predictions that respond to users evolving needs
  • Oversee the maintenance and support of operational ensemble systems, ensuring that issues arising in production are investigated and addressed promptly
  • Foster effective collaboration across ECMWF, with Member and Co‑operating and with the wider scientific and operational community, representing ECMWF where appropriate

Education

Advanced university degree or equivalent professional experience

Job description

Your role

Ensemble prediction is central ECMWF’s operational forecasts and products. Reliable probabilistic forecasts enable users in Member and Co-operating States and beyond to understand forecast uncertainty and make better-informed decisions.


We are seeking a Team Leader for the newly formed Ensemble Modelling Team, which will lead ECMWF’s work on ensemble prediction across medium-range, sub-seasonal, seasonal and longer-range applications.


The role offers a unique opportunity to shape the future of ECMWF’s ensemble prediction capabilities. You will guide the design and development of physics-based, AI-based and hybrid ensemble systems, determine how different approaches can best contribute to reliable probabilistic forecasts, and help ensure that scientific advances are translated into robust operational forecasting systems that respond to evolving user needs.


As Team Leader, you will provide scientific and managerial leadership for a team of around a dozen experienced scientists. Reporting to and supporting the Head of Earth System Modelling, you will help set priorities, plan and manage the team’s programme of work. You will also foster effective collaboration across ECMWF and with Member and Co-operating states.


About the Ensemble Modelling Team

The Ensemble Modelling Team will be part of the Earth System Modelling Section in ECMWF’s Research Department. It will consolidate and advance ECMWF’s operational ensemble prediction systems across medium-range, sub-seasonal, seasonal and longer-range applications.


The team will be responsible for ensemble configuration design, initialisation, representation of model and initial‑condition uncertainty, calibration and reliability. Its work will span physics-based, AI-based and hybrid systems, sharing methods across timescales where relevant and tailoring approaches to different prediction ranges where needed.


The team will also maintain, support and further advance ECMWF’s operational ensemble systems, using numerical experimentation to guide improvements and address issues that may arise in operations. It will work with colleagues across data assimilation, atmospheric, ocean and land modelling, machine learning, evaluation, forecast production and user services to support the delivery of world‑leading ensemble predictions.


Your responsibilities

As Team Leader, you will:



  • Lead and manage the Ensemble Modelling Team, setting objectives and priorities, supporting effective delivery, coaching and developing team members

  • Work with the Head of Earth System Modelling to shape the scientific direction for ensemble prediction across medium-range, sub‑seasonal, seasonal and longer‑range applications, leveraging physics‑based, AI‑based and hybrid approaches

  • Guide the design and further development of ECMWF’s operational ensemble prediction systems to support the delivery of world‑leading operational ensemble predictions that respond to users evolving needs

  • Oversee the maintenance and support of operational ensemble systems, ensuring that issues arising in production are investigated and addressed promptly

  • Foster effective collaboration across ECMWF, with Member and Co‑operating and with the wider scientific and operational community, representing ECMWF where appropriate


What we are looking for

We are looking for someone who combines deep scientific expertise in ensemble prediction with practical, supportive leadership. You will be comfortable leading experienced scientists, making clear choices across a broad programme of work and establishing a common direction across prediction ranges and modelling approaches.


You will bring:



  • An inclusive and decisive leadership style, with the ability to empower and develop team members.

  • Excellent scientific judgement and confidence to help shape direction and establish clear priorities.

  • The ability to take a cross‑timescale view of ensemble prediction, identifying where common approaches can be used and where different solutions are needed.

  • The ability to build trust and manage dependencies across scientific, technical, operational and user‑facing teams

  • Strong listening and communication skills, including the ability to understand different user perspectives and represent ECMWF effectively.

  • Strong organisational skills and the flexibility and resilience to lead a complex and evolving programme of work, including when priorities change or operational issues arise


Your profile

Education



  • An advanced university degree or equivalent professional experience, in a relevant field


Essential experience and knowledge



  • A substantial track record in ensemble prediction and probabilistic forecasting

  • Significant experience developing operational medium‑range, sub‑seasonal or seasonal forecasting systems, using physics‑based and/or AI‑based approaches

  • Demonstrated scientific and people leadership, including setting priorities and leading complex programmes and experienced teams


Desirable experience and knowledge



  • Understanding of operational forecasting requirements and evolving user needs

  • Knowledge of ensemble forecast evaluation and its use in guiding ensemble system development

  • Experience with ensemble calibration, or the design of probabilistic products


Languages


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


If you feel that you have the motivation and many of the skills for this role but don't meet precisely all of the criteria listed above, we still encourage you to apply.


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.


The success of our activities depends on the funding and partnerships of our 35 Member and Co‑operating States who provide the support and direction of our work. Our talented staff together with the international scientific community, and our powerful supercomputing capabilities,are the core of a 24/7 research and operational centre with a focus on medium and long‑range predictions. We also hold one of the largest meteorological data archives in the world.


Our vision: World‑leading monitoring and predictions of the Earth system enabled by cutting‑edge physical, computational and data science, resulting from a close collaboration between ECMWF and the members of the European Meteorological Infrastructure, will contribute to a safe and thriving society


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


In addition, ECMWF has established 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, as well as being a contributor 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.


ECMWF is a multi‑site organisation, with its headquartersin Reading, UK, a data centre in Bologna, Italy, and a large presence in Bonn, Germany as a central location for our EU‑related activities.ECMWF is internationally recognised as the voice of expertise in numerical weather predictions for forecasts and climate science.


www.ecmwf.int


About Copernicus copernicus.eu


About Destination Earth destine.ecmwf.int


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. Information about working with us and full details of salary scales and allowances are available on the ECMWF website at:


www.ecmwf.int/en/about/jobs/working-ecmwf.


Starting date: asap


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) will be conducted in English and are expected to take place approximately a month after the closing date.


Successful applicants and members of their family forming part of their households will be exempt from immigration restrictions.


Who can apply

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.


ECMWF Member and Co‑operating States are: 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 (note: ECMWF will not be able to assist with leaving the country). Applications from nationals from other countries may be considered in exceptional cases.

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