Scientist for Machine Learning

Scientist for Machine Learning

United Kingdom 10 Mar 2021


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State University
Host Country
10 Mar 2021
Study level
Opportunity type
Opportunity funding
Full funding
Eligible Countries
This opportunity is destined for all countries
Eligible Region
All Regions

1.  Position information

Vacancy No.: VN21-02

Department: Research

Grade: A2

Section: -

Job Ref. No.: STF-C/21-02

Reports to: AI and Machine Learning Coordinator

Publication Date: 4 February 2021

Closing Date: 10 March 2021

Location: Reading or Bonn

2.  About ECMWF

ECMWF is both a research institute and a 24/7 operational service, producing numerical weather predictions for its Member and Co-operating States as well as users around the world. ECMWF carries out scientific and technical research and analysis aiming to continuously improve global prediction. ECMWF processes in its high-performance computing facility large amounts of observations to provide up-to-date global analyses and climate reanalyses of the atmosphere, ocean and land surface. For details, see

Over the years, ECMWF’s partnership with the European Union has grown, and in 2014 ECMWF became an entrusted entity to operate the Copernicus Atmosphere Monitoring Service (CAMS) and the Copernicus Climate Change Service (C3S) on behalf of the European Commission until mid-2021 and ECMWF is preparing plans for the next phase of the Copernicus Programme for the period 2021-2027.

ECMWF currently operates from its headquarters, located in Reading, UK, and its data centre located in Bologna, Italy. Over the course of 2021, ECMWF will be opening additional new premises in Bonn, Germany.

ECMWF has embarked on an exciting new initiative to explore the use of artificial intelligence and machine learning in applications of numerical weather predictions. To learn more about future plans for machine learning at ECMWF, please have a look at our machine learning roadmap: and To learn more about the application of machine learning in the weather and climate domain in general, please refer to the webpage of the Machine Learning Seminar Series at ECMWF ( or the recordings of the ESA-ECMWF machine learning workshop (

3. Summary of the role

The successful candidate will play an essential role in the development of customised machine learning applications for several application areas at ECMWF. This will involve much interaction with domain scientists in providing both advice and support in the development and implementation of machine learning tools, and the efficient link between new machine learning tools and the existing numerical weather prediction workflow. These tasks will be supported by existing efforts at ECMWF to establish an efficient machine learning workflow for weather and climate models including the CliMetLab tool (, the new Centre of Excellence between ATOS and ECMWF (, and the MAchinE Learning for Scalable meTeoROlogy and climate (MAELSTROM) EuroHPC Joint Undertaking project which is coordinated by ECMWF.

4.  Main duties and key responsibilities:

5.    Personal attributes

6.  Qualifications and experience required



Knowledge and skills (including language)

7.  Other information

Grade remuneration

The successful candidate will be recruited at the A2 grade, according to the scales of the Coordinated Organisations. The annual basic salary if based in the UK will be £62,166.00 net of tax. The annual basic salary if based in Germany will be EURO 75,178.92 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, 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 role can be located in the Reading area, in Berkshire, United Kingdom, or at ECMWF’s duty station in Bonn, Germany. With the duty station in Bonn currently expected to open in summer 2021, the successful candidate may be asked to start in Reading initially.

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

Videoconference interviews (via Blue Jeans) are expected to take place at the end March 2021.

8.  How to apply

Please complete the online application form available at:

To contact the ECMWF Recruitment Team, please email

Please refer to the ECMWF Privacy Statement. For details of how we will handle your personal data for this purpose, see:

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 France, Hungary, Germany, Greece, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Morocco, the Netherlands, North Macedonia, Norway, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom.

Applications from nationals from other countries may be considered in exceptional cases.

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