20 computer-security "https:" "https:" "https:" "https:" uni jobs at European Space Agency in Netherlands
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on the development and qualification of secured GNSS satellite-based augmentation systems (SBAS) for safety-of-life applications. In particular, the team is responsible for the development of the European
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its role as Design and Procurement Agent, under the programme management of the European Commission (EC). Version 3 of the system is currently under procurement under Phase CD. The Division is also
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systems. Candidates interested are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship Topic of the internship: NAV-SP Unclassified automatic documentation
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, Connectivity, and Navigation, aiming to transform Europe’s ability to act autonomously in matters of crisis response and civil security. Candidates interested are encouraged to visit the ESA website: http
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Space Agency (ESA) is leading a programme to advance the European capabilities for developing a LEO-PNT system and support Europe in remaining a leader in the world-wide space-based positioning
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Location ESTEC, Noordwijk, Netherlands Our team and mission You will join the Galileo Programme Office, part of the Galileo and EGNOS Programme Department within the Directorate of Navigation
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and Procurement Agent, under the programme management of the European Commission (EC). Phase CD of Version 3 of EGNOS system is currently under development. EGNOS (European Geostationary Navigation
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its role as Design and Procurement Agent, under the programme management of the European Commission (EC). Version 3 of the system is currently under procurement under Phase CD. The Division is also
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support in the management and implementation of the Advanced Research in Telecommunications Systems (ARTES) Programme, under the Directorate of Connectivity and Secure Communications. The team plays a key
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are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship You can choose between the following topics: 1) Topic 1: Machine Learning for recognition of planetary materials