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Scientist for Machine Learning

Bonn

  • Organization: ECMWF - European Centre for Medium-Range Weather Forecasts
  • Location: Bonn
  • Grade: A2 - Grade band
  • Occupational Groups:
    • Education, Learning and Training
    • Information Technology and Computer Science
    • Scientist and Researcher
    • Innovations for Sustainable Development
  • Closing Date: 2022-07-05

Job reference: VN22-42

Location: Bonn, Germany

Deadline for applications: 05/07/2022

Publication date: 08/06/2022

Salary and Grade: Grade A2: EUR 78,035.40 basic salary, net of tax + other benefits

Contract type: STF-PL

Department: Computing

Contract Duration: 30 months, with possibility of extension to 31 May 2025 subject to available funding

ECMWF is the leading centre for global, medium-range weather predictions and is the host of the largest archive of weather data in the world. ECMWF is both a research institute and a 24/7 operational service, producing and disseminating numerical weather predictions to its Member States. ECMWF has also been entrusted to operate the Copernicus Atmosphere Monitoring Service (CAMS) and the Copernicus Climate Change Service (C3S) on behalf of the European Commission. ECMWF in partnership with ESA and EUMETSAT is participating to the implementation of the DestinE program, funded by the European Commission’s Digital Europe programme.

Every day, hundreds of millions of satellite and in situ observations are processed at ECMWF to provide the basis for up-to-date global analyses and climate reanalyses of the atmosphere, ocean and land surface, and to generate global weather predictions from hours up to a year ahead. To retain its world-leading position, ECMWF is performing cutting edge research in weather related sciences and high-performance computing. ECMWF’s weather forecasts are disseminated to the ECMWF Member States and thousands of users around the world.

ECMWF has recently become a multi-site organisation, with its headquarters based since its creation in Reading, UK, its new data centre in Bologna, Italy, and new offices in Bonn, Germany.

It has also recently adopted a hybrid organisation model which allows its staff to mix both office working and teleworking. This generous and flexible model provides our staff with considerable flexibility to spend time outside or away from their duty station and decide how they wish to manage their professional working time at ECMWF. ECMWF is an organisation that values the whole being and both understands and values the need for flexibility in the way its staff work.

For additional details, see www.ecmwf.int.

ECMWF in the recent years has embarked on an initiative to explore the offering of Cloud Computing services and to make available cloud resources close to its data and existing HPC and storage infrastructure. In the context of this effort, ECMWF is participating in the EO4EU Horizon Europe project which aims to provide innovative tools, methodologies and approaches that would assist a wide spectrum of users, from domain experts and professionals to simple citizens to benefit from Earth Observation (EO) data.

EO4EU will deliver dynamic data mapping and labelling based on AI adding FAIRness to the system and data. EO4EU will introduce an ecosystem for holistic management of EO data, bridging the gap among domain experts and end users, bringing in the foreground technological advances to address the market straightness towards a wider usage of EO data. EO4EU envisages to boost the Earth Observation data market, providing a digestible data information model for a wide range of EO data, through dynamic data annotation and a state-of-the-art serverless processing by leveraging important European Cloud & HPC infrastructures.

This role will contribute to the AI4copernicus project (https://ai4copernicus-project.eu/) until its completion until the end of 2023. The ECMWF contribution to the project is in the development of customised ML models relating to health and wellbeing and also to supervise the progress of projects funded by the open calls of AI4Copernicus project (through cascade funding). 

The successful candidate will apply their skills, knowledge, and expertise to help achieving the goals, complete the deliverables of the EO4EU and AI4Copernicus projects and also contribute to other related activities within the organization.  It is anticipated that the duties for this position may change and evolve over time, to address the changing needs of ECMWF and its Member States.


  • Contributing to the EO4EO project management and related activities i.e., prepare reports, dissemination and technology transfer activities of the EO4EU project
  • Contributing to the formulation of the high-level design and implementation principles to enable the EO4EU ecosystem to access the underlying infrastructure provided by multiple data pools as a common pool of resources
  • Contributing in the design and implementation of generic ML pipelines which will use the available input data sources of EO data to process and serve downstream tasks
  • Contributing in the development of ML models to reduce the data volume that will be transferred
  • Strong interpersonal and communication skills, particularly listening to and respecting the views of others
  • Enthusiasm to tackle challenging research questions when working with complex technical tools and the willingness to learn new algorithms, technologies, and methodologies
  • Ability to work in a team at ECMWF and within EO4EU towards a common goal in an interdisciplinary research project
  • Excellent analytical and problem-solving skills with an independent and proactive approach, together with an interest in identifying, investigating, and solving technical challenges

Education:

  • A university degree, or equivalent, in a discipline related to computer science, physics, mathematics, ML or engineering is required
  • A PhD in a related subject is desirable but not essential

Experience:

  • Experience in developing ML techniques and knowledge extraction
  • Experience in ML techniques related to Earth System data orchestration would be advantageous.
  • Experience in using Python for EO data, in particular machine libraries such as TensorFlow or Keras, would be advantageous

Knowledge and Skills 

  • Ability to work in a Linux-based environment
  • A good understanding of Cloud technologies and be comfortable working in Cloud (either community or public deployments) environments
  • A good knowledge of developing and deploying ML code in containers and Kubernetes clusters
  • Previous experience in participating in EC funded projects would be an asset
  • A good knowledge of Python and Jupyter notebooks would be useful

Language

  • 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

Grade remuneration

The successful candidate will be recruited at the A2 grade, according to the scales of the Co-ordinated Organisations and the annual basic salary will be EUR 78,035.40 basic salary, net of tax. ECMWF also offers a generous benefits package, including a flexible teleworking policy. The position is assigned to the employment category STF-PL as defined in the ECMWF Staff Regulations. Full details of salary scales and allowances available on the ECMWF website at www.ecmwf.int/en/about/jobs, including the ECMWF Staff Regulations and the terms and conditions of employment.

Starting date:  01 September 2022 or as soon as possible.

Length of contract: The contract duration is expected to be 30 months with the possibility of extension up to 31 May 2025, subject to available funding

Location: The position will be located at ECMWF’s duty station in Bonn, Germany.

As a multi-site organisation, ECMWF has adopted a hybrid organisation model which allows flexibility to staff to mix office working and teleworking.

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

Interviews by videoconference (Via Teams) are expected to take place in mid-July 2022.

Applicants are invited to complete the online application form by clicking on the apply button below.

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, as well as from all EU Member 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, Turkey and the United Kingdom.

In these exceptional times, we also welcome applications from Ukrainian nationals for this vacancy.  

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

 

We do our best to provide you the most accurate info, but closing dates may be wrong on our site. Please check on the recruiting organization's page for the exact info. Candidates are responsible for complying with deadlines and are encouraged to submit applications well ahead.
Before applying, please make sure that you have read the requirements for the position and that you qualify.
Applications from non-qualifying applicants will most likely be discarded by the recruiting manager.
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