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will develop novel and privacy-preserving algorithms that allow distributed devices (smartphones, wearables) to learn from new data streams over time (Continual Learning) while collaborating globally
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planning, and explainable decision support. The PhD will operate across two worlds: The University of Twente — advancing scientific models, algorithms, and hybrid AI methodologies; Thales (the industrial
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implementation and evaluation of a live prototype: a server-based, functional digital platform that integrates the soundscape assessment algorithms and can be tested both in controlled environments and in-situ
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are not limited to): Machine learning and artificial intelligence applied to astronomical data Advanced statistical and probabilistic inference methods Scalable algorithms for the analysis of large
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mentoring of members of our research network, as well as outreach activities, all generally related to your research topic though not exclusively. You are encouraged to visit the ESA website: https
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to the research; Good understanding of computer architecture; Basic understanding of MRI algorithms is a plus; Understanding of AI and its practical implementations; The ability to work in a team and take
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responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with stakeholders Development of open
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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