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intelligence, for example for machine learning and predictive maintenance and on-board and on-ground flight data processing; developing an artificial intelligence strategy for European launcher manufacturing
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Education A master’s degree in telecommunications, electrical or computer engineering is required for this post. A PhD in a relevant domain would be considered a plus. Additional requirements General
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methodologies, such as additive manufacturing, for projects within the centre and for space exploration; Developing new ideas around medical technologies, for example, using machine learning techniques to support
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also assist in evaluating the most suitable spectral identification methods for planetary materials using custom classification software based on Machine Learning techniques. Key tasks include collecting
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to develop your professional experience and competencies, to learn from ESA experts and to contribute to ESA activities. Technical competencies Experience with artificial intelligence and machine learning
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for systematic reviews, Mendeley for citation management and SPSS for data/statistical analysis/machine learning. Diversity, Equity and Inclusiveness ESA is an equal opportunity employer, committed to achieving
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and strong preference for also excellent Dutch language skills. You’re able to adapt and learn quickly, you like to turn your ideas into action and are able to work independently. Strong detail
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business card) Discount on membership of Erasmus Sport. Access to online learning platform GoodHabitz and wellbeing platform OpenUp. Regular fun work events and drinks. Participation in our collective
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performance in accordance with the respective service level and application of internal processes. This includes contributing to risk management definition, mitigation actions and lessons learned exercises
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required. Experience with the design, development and verification of TT&C and PDT subsystems for space applications is required. Very good knowledge of modern computer systems, simulation and modelling