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responsibilities will include: Design and develop analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN
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neuromorphic ultra-low-power active sensor readout and processing at the edge. The chip design will enable online learning capabilities, aiming at modulating the spatio-temporal filtering properties with
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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, evolución e integración como servicio de simuladores de planificación de misión de drones, sensores de medidas antidron y simulación de infraestructuras críticas. Colaboración en el desarrollo de componentes
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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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point-of-care spectroscopic sensor to determine the impact of the cell therapy during orgran perfusion. This includes generating experimental data sets with a commercially available spectrometer
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simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power consumption and
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different hardware backends. Design conventional (GPU-based) deep neural networks for comparison. Publish research articles, regular participation in top international conferences to present your work
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. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming
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. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent