Team Leader - Ensemble Modelling

Salary and Grade: Grade A3, Reading, UK: £94,251 or Bonn, Germany: €113,224 NET annual basic salary + other benefits

Deadline for applications: 07/09/2026

Location: Reading, UK or Bonn, Germany

Contract Duration: Four years, with the possibility of future contracts

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.