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for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive
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) radiation sensors Assembly and characterization of SiC sensor modules for laboratory and beam tests measurements Development and characterization of analog and digital electronics for high dynamic range
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high-impact inventions in analog filters, thermal noise cancelling amplifiers, ultra-low power analog to digital converters, software-defined radio, mixer-first receivers, N-path filters and sub-sampling
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the structure and texture of High Moisture Extrudates (HME), Plant-based Dry Cured Meat Analogs (Pb-DCMA), and Dry Cured Ham (DCH) by investigating their characteristics at molecular, microscopic, and macroscopic
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neuromorphic hardware, this project will push into next-generation analog circuits and memristive devices, in collaboration with PGI-14. The goal is to train a system that leverages the intrinsic non-linear
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 1 day ago
workflow based on this kind of platform: Analog Audio Inputs/Microphones → DNN Inference on Embedded NPU → Analog Audio Outputs/Speakers. In a second phase, various classes of algorithms will be run
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for the best algorithm-hardware pair for a given problem. While we have a history of success in optimizing digital neuromorphic hardware, this project will push into next-generation analog circuits and
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. The system will include: A very compact, ultra-low-power analog front-end (AFE) to sense neural signals. An on-chip neuromorphic processor to convert the neural data into spike-based encoded data and
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-on-rfmicrowave… Requirements Specific Requirements You are a self-motivated and enthusiastic researcher; You have an MSc degree with excellent grades in Electrical Engineering, with a specialization in Analog, RF
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-design SSM-inspired spiking neural network (SNN) cores and integrate them with a low-power RISC-V processor. The PhD candidate will develop spike-based computing blocks and explore hybrid analog/digital