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Recognition Machine Learning and Pattern Recognition are subareas of AI aimed at the development of algorithms and models capable of learning from data, recognizing patterns, and signal analysis. Tasks include
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at the development of algorithms and models capable of learning from data, recognizing patterns, and signal analysis. Tasks include image and speech recognition, recommendation systems, and predictive analytics
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Research and Development (R&D) Unit. Our R&D Units are the cornerstone of the Institute’s organizational structure. These units may focus on either foundational methods or application domains and are
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will develop a method to help development teams choose the right algorithm and right hardware. This can be done by measuring (during the above-mentioned experiments) how the algorithms are constrained
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Systems for hydrogen) studies the development of hydrogen systems from a socio-technical perspective. It considers both the economic and business cases of hydrogen systems, but also the system integration
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multiscale analysis of the mass distribution, as well as that of the flow field structure, and of the force and tidal field that has been shaping the cosmic web. The basic detection algorithms to infer
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of Earth observation, navigation, science, and connectivity and secure communications. The AOCS and Pointing Systems Section carries out technological research and development, harmonisation and
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partners. The successful applicant is expected to carry out research on the algorithmic foundations of digital platforms for large-scale deliberation. The research has the potential to directly inform the
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a large interdisciplinary consortium of digital democracy researchers as well as several societal partners. The successful applicant is expected to carry out research on the algorithmic foundations
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structure, and of the force and tidal field that has been shaping the cosmic web. The basic detection algorithms to infer the overall structure of the cosmic web are the various versions of the scale-space