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project FADOS focusing on a holistic approach of doping in organic electronics. The European Marie Sklodowska-Curie Innovative Training Network FADOS brings together 11 academic institutions, including
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. Machines must be equipped in-situ with smart sensors and supported by systems that can process such as images and time series, in real time. Machine learning and AI have become essential for driving
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Networks in order to handle non-linear relationships between covariates and response variables. To this aim, the PhD student will join a consortium of researchers issued from different disciplines with a
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), and therefore, in accordance with regulations, requires that your arrival be authorized by the competent MESR authority. Liquid flows in vascular networks are among the most effective ways to transport
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role in intracellular transport. As such, they play an important role in nuclear positioning. Our team is studying, in a developmental context, how multiple microtubule networks cooperate to position
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medicine. The laboratory benefits from a large network of national and international collaborations and access to cutting-edge technological platforms, including advanced microscopy, high-throughput
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sensors and power electronics [1]. With recent advances in diamond synthesis techniques, new opportunities have emerged for quantum-scale applications, including in high-pressure and biomedical physics
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optimization of complex systems, intelligent data and information systems, as well as networks, distributed systems, and security. LIMOS stands out for its interdisciplinary approach, combining theoretical
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. Organic electronics offer a promising alternative to inorganic electronics for large-area applications, particularly in displays and flexible sensors. Among these devices, Organic Thin-Film Transistors
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 7 days ago
, 3], significant challenges related to running complex AI algorithms such as Deep Neural Network (DNN) inference on lightweight platforms with limited computational power and relying on potentially