Internet of Things devices and other devices with environmental sensors are ubiquitous. The data that they collect are potentially hugely scientifically valuable for forecasting, but they are totally unlike anything that has been used in this domain previously. They are hugely numerous, typically small and high-frequency, but not calibrated or handled with the care taken by formal observation stations.
As Research Software Engineer – IoT and Observation Handling (A2), you will be responsible for building a novel data infrastructure to handle unconventional observational data from private and public sensors, crowd sourced data, and Internet of Things (IoT). You will develop the technology and systems to perform quality control, encode observations in standardised forms, and store and index the observations before making them available to external partners through a web service. The data will need to follow standards including OGC, FAIR data, and European Data Governance. The technology should as far as possible be made generic and scalable and connect to the existing software tools in ECMWF’s production chain.
You will work in the Data Management Services team in the Development Section. We are responsible for all software and systems handling meteorological data from when they arrive at ECMWF to when they leave. This includes high-throughput specialist software that supports the operational forecast model, systems for acquisition of incoming observations, management of direct model output, and the perpetual archival of forecasts and observations. We particularly focus on the use of semantically meaningful metadata to route and control data flows, and on novel systems and methods to address the disruptive changes coming.
The work will be carried out in the AD4GD, TRIGGER and DaFab projects. AD4GD aims to co-create and shape the European Green Deal Data Space as an open hub for FAIR data, and TRIGGER looks at impacts on human health from weather and climate hazards incorporating novel geophysical and health-related observations. DaFab aims to use AI and federated computing techniques to analyse Earth Observation datasets to support real-time applications. Additionally, there is overlap with iCHANGE (individual Change of Habits Needed for Green European transition, H2020), aiming to raise awareness of climate issues by making it easier to observe the environmental impacts of human activities.
About ECMWF
The European Centre for Medium-Range Weather Forecasts (ECMWF) is a world-leader in weather and environmental forecasting. As an international organisation we serve our members and the wider community with global weather predictions and data that is critical for understanding and solving the climate crisis. We function as a 24/7 research and operational centre with a focus on medium and long-range predictions, holding one of the largest meteorological data archives in the world. The success of our activities builds on the talent of our scientists and experts, strong partnerships with 35 Member and Co-operating States and the international community, some of the most powerful supercomputers in the world, and the use of innovative technologies and machine learning across our operations. ECMWF is a multi-site organisation, with a main office in Reading, UK, a data centre/supercomputer in Bologna, Italy, and a large presence in Bonn, Germany.
ECMWF has also developed a strong partnership with the European Union and has been entrusted with the implementation and operation of the Destination Earth Initiative and the Climate Change and Atmosphere Monitoring Services of the Copernicus Programme. Other areas of work include High Performance Computing (HPC) and the development of digital tools that enable ECMWF to extend provision of data and products covering weather, climate, air quality, fire and flood prediction and monitoring.
Apply at: https://jobs.ecmwf.int/Job/JobDetail?JobId=285
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