Scientist - NWP Software Developer

About ECMWF

ECMWF is both a research institute and a 24/7 operational service, producing and disseminating numerical weather predictions to its Member States. ECMWF carries out scientific and technical research directed to the improvement of its forecasts, collects and processes large amounts of observations, and manages a long-term archive of meteorological data. Satellite and in situ observations provide the information for up-to-date global analyses and climate reanalyses of the atmosphere, ocean and land surface. For details, see www.ecmwf.int/.

Summary of the role

This role is in the Code Efficiency Team of the Integrated Forecast Systems (IFS) Section in the Research Department. The IFS is ECMWF’s world-leading global data assimilation and numerical weather prediction system, used to provide medium-, extended- and seasonal-range forecasts, global re-analyses, and atmospheric composition monitoring, to Member States across Europe as well as commercial customers around the world.

The IFS Section is responsible for all technical aspects of the IFS, from the build system and the merging of new contributions, through to the handover of new releases to operations and the management of the research data archive.

The Code Efficiency team has a very important part to play in optimising efficiency of both the operational suites and the research workload, to ensure rapid scientific progress can be made cost-effectively, and in adapting the IFS for future HPC architectures.

The successful candidate will participate in the work of the Code Efficiency Team. In particular, he or she will maintain and develop the IFS build system and the associated automated testing framework and quality-assurance test suite.

Another key element to this function will be to support scientists across the organisation, with a focus on observation processing and data assimilation, in developing, optimising, debugging and testing new contributions to the IFS.

Main duties and key responsibilities

• Improving the software design and implementation of ECMWF’s modelling and data assimilation systems
• Maintaining the build system for the IFS forecast system
• Maintaining and evolving observation-processing code bases with emphasis on code efficiency and software quality
• Supporting other scientists involved in observation processing and data assimilation development with optimisation, problem-solving and advice on software-related aspects • Assisting with the testing and debugging of different configurations of new IFS releases

Personal attributes

• A desire to improve software development processes, tools and procedures and advocate improvements to others
• Good interpersonal and communication skills, listening to and respecting the views of others
• Good analytical and problem-solving skills with a proactive approach, together with an interest in identifying, investigating and solving technical problems.
• Dedication and enthusiasm to work in a small team, and ability to lead technical activities within a team
• Ability to work under pressure to solve operational problems and meet project deadlines
• Interest in a broad range of technical areas and a willingness to contribute to wider team activities

Qualifications and experience required

Education

• A university degree, or equivalent, in a discipline related to physics, mathematics, or computer or computational science. A PhD is desirable but not essential.

Experience

• Experience working with scientific codes on high-performance computers in a research environment is essential.
• Experience working on the software-engineering aspects of scientific codes (e.g. build systems, version control, testing frameworks, development processes, etc.) would be a distinct advantage.
• Experience supporting scientific researchers in developing new modelling capabilities and solving modelling problems would be an advantage.
• Experience working in numerical weather prediction would be an advantage

Knowledge and skills (including language)

• In-depth, detailed knowledge of Fortran, MPI and OpenMP is essential.
• High-level of competence in a Linux environment is essential.
• Knowledge of the CMake build script generator would be a distinct advantage.
• Knowledge of observation-handling systems or observation data formats for NWP would be a distinct advantage.
• Knowledge of C/C++ would be an advantage.
• 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) would be an advantage.

Other information

Grade remuneration

The successful candidate will be recruited at the A2 grade, according to the scales of the Coordinated Organisations and the annual basic salary will be £58,238.40 net of tax. This position is assigned to the employment category STF-C as defined in the Staff Regulations. Full details of salary scales and allowances are available on the ECMWF website at www.ecmwf.int/en/about/jobs, including the Centre’s Staff Regulations regarding the terms and conditions of employment.

Starting date: As soon as possible.

Length of contract: Four years with the possibility of a further contract.

Location: The position will be based in the Reading area, in Berkshire, United Kingdom.

How to apply

Please apply by completing the online application form available at www.ecmwf.int/en/about/jobs. 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.

Staff are usually recruited from among nationals of the following Member States and Co-operating States: Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, former Yugoslav Republic of Macedonia, France, Hungary, Germany, Greece, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, Norway, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom. Staff from other countries may be considered in exceptional cases.