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streaming data required by modern AI algorithms... Where to apply Website https://lavoraconnoi.unitn.it/contratti-di-ricerca/dipartimento-di-ingegneria-e… Requirements Additional Information Eligibility
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network aims to deliver fiber-optic quality experiences over wireless links by building the theoretical, algorithmic, and architectural foundations of THz systems. It introduces ultra-MIMO (multiple-input
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methodologies for measuring social and environmental impact. The main activities will include analyzing available impact data sources, designing models for impact assessment, and developing algorithms
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networks. The activities will include the development of algorithms for processing seismic and geodetic signals, subsurface imaging, dynamic characterization of sites and structures, as well as monitoring
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. The candidate will work on wind turbine and wind farm control, developing innovative control algorithms and validating them through wind tunnel testing. The candidate will also be responsible for teaching
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of mathematical models of biological processes or phenomena, in the presence and absence of pathologies. - - Development and validation of algorithms for the processing of diagnostic biosignals, also using
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a big plus: Relevant publications (and/or M.Sc. thesis) on the above-mentioned research topics Programming Microcontrollers and Interfacing Sensors Machine Learning Algorithms and Deep Neural Networks
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at the Edge (CAITE) whose aim is twofold. First, it aims to bring AI at the edge, by providing scalability and resource efficiency through the development of cooperative, distributed AI algorithms, optimising
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clustering algorithms. 2) M20 / Duration 3 months/ SCM (Amsterdam (NL) (supervisor at hosting institution: Stan van Gisbergen) Goal: acquire experience on specific features of BAND and new VCD code. Training
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, the selected researchers will deal with: Research & Development: Designing, developing, and implementing state-of-the-art machine vision and deep learning algorithms to analyze complex image and sensor data