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element of embedded intelligence lies in the sensor's ability to self-calibrate and, in particular, to adapt its responses and models according to sensor aging and the (sometimes significant) variability
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queries within embedded knowledge graphs. It will involve designing or adapting efficient indexing structures tailored for vector databases and exploring hybrid neurosymbolic techniques to enhance query
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role in models of pulmonary disease. The research is embedded in a Franco–Brazilian collaboration at the interface of immunology and structural biology, providing exposure to complementary expertise and
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to participate in the design, fabrication and characterization of bulk acoustic wave (BAW) devices. The PhD student will be embedded in the Acoustics and Microelectronics teams of the Institute
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demonstration. Specifically: • Composite demonstrators will be manufactured by embedding lignin fibers into bio-based matrices, replacing glass fibers with lighter, more sustainable reinforcements. • Filtration
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representative of the geometry of a storage tank. To do this, embedded instrumentation using fiber Bragg gratings (FBG) will be implemented. • The third and final part aims to establish the link between