ECMWF – Scientist for Machine Learning

ECMWF, Shinfield Park, UK or ECMWF’s duty station in Bonn, Germany
Closing date: 31 January 2021

ECMWF has embarked on an exciting new initiative to explore the use of artificial intelligence and Machine Learning (ML) in applications of numerical weather predictions and provide the developed tools and techniques to the public. As part of this effort, ECMWF is participating in the AI4Copernicus H2020 project which funds this position.

This position will be in the Computing Department which coordinates ECMWF’s participation to the project. The successful candidate will apply their skills, knowledge, and expertise to help achieving the goals, and complete the deliverables of the AI4Copernicus project. The main focus will be on the development of supervised ML techniques such as Convolutional Neural Networks, Generative Adversarial Networks, Recurrent Neural Networks and Long-Short Term Memory (LSTM) networks that will be developed for the AI4Copernicus platform for the analysis of single-date and time series of remote sensing images to serve the user cases of AI4Copernicus in the area of agriculture, energy, security and health.

The main responsibility of ECMWF’s contribution is in the development of customised ML models relating to health and wellbeing. This includes predictions of pollution based on a mixture of local observations and three-dimensional data of the atmosphere using three dimensional convolutional neural networks as well as the detection of Earth Observation (EO) related features such as warm spells related to diseases such as Malaria.

The successful applicant will also contribute to knowledge extraction from EO data using unsupervised learning and will support open calls from AI4Copernicus. The Scientist will work in close collaboration with other teams across the organisation and strong communication skills are essential.

Main duties and key responsibilities

  • Developing supervised ML techniques for the analysis of single-date and time series of remote sensing images
  • Developing customised ML solutions pertaining to health and wellbeing in the context of Earth System science
  • Contributing to reports, dissemination and technology transfer activities of the AI4Copernicus project

Other information
The successful candidate will be recruited at the A2 grade, according to the scales of the Co-ordinated 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-PS 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: 1 March 2021, or as soon as possible thereafter.
Length of contract: 22 months, subject to available funding with possibility of extension.
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 start in Reading initially.


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