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firmware design. Contact: Massimo Gottardi (FBK), Giampietro Tecchiolli (AI4IV) Where to apply Website https://phd.fbk.eu/calls/detail/mixed-analog-digital-cmos-architectures-for-ai-… Requirements Research
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archaeological signatures (e.g., micro-relief, edge structures, etc.) – Design and implementation of new deep learning architectures (both supervised and unsupervised/few-shot, 2D and 3D) for an efficient and
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sensors. The architecture integrates (i) an ultra-low form factor microfluidic separation module and (ii) a multi-modal SiC sensor for precise analyte identification. The seamless integration of a
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-based design to manage architectural complexity, automated generation of safety artifacts (such as Fault Trees and FMEA), and formal verification of FDIR strategies. Furthermore, the research will explore
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–microfluidic platforms capable of generating and manipulating synthetic chiral light Explore novel photonic architectures and materials for enhanced light confinement and sensing performance Collaborate with