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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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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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(UQ) for machine learning and its validation. Your areas of research will be chosen based on both your own expert judgement and insight into trends and developments and on team requirements to ensure
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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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