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Join TU Delft and work together with NXP to build low-power AI accelerators for self-healing analog/RF calibration, fixing noise/offset. Co-design algorithms & hardware and validate on real silicon
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Charalampopoulos, focuses on the molecular mechanisms of cell survival and regenerative capacity in the adult nervous system. The lab emphasizes neurotrophins and their receptors, develops novel analogs
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to the conserved neural organization of the mammalian brain, which provides a common computational blueprint across species despite profound differences in body plan and ecological niche. Motivated by this analogy
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Department of Human Centered Design (HCD https://www.human.cornell.edu/hcd ) enriches people and their environments through transdisciplinary research, teaching, and outreach. We integrate analog and digital
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recovery mechanisms will also be evaluated and integrated, addressing the susceptibility of analog and in-memory computing to noise, process variation, and soft errors. The primary objective is to design a
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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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. 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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Location: Stockholm, Stockholm 10691, Sweden Subject Area: Condensed Matter Physics / Superfluidity and superconductivity Appl Deadline: (posted 2025/09/08, listed until 2025/10/04) Position Description
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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
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to optimize performance and interpretability, analogous to RAG (Retrieval-Augmented Generation) in LLMs Investigating multiple models for analysis, focusing on the Occam’s Razor principle of preferring simpler