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), Department for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI Dresden) the Chair of Adaptive Dynamic Systems offers a position as PhD Student / Research Associate in FPGA Design for AI
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for this PhD position will be conducted in the research team on Intelligent Wireless Networking. Job description Wireless systems are omnipresent in our daily life, but it is far from perfect, especially
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emerging models by collaboratively exploring various computation models leveraging physical devices properties. This PhD work will focus on FPGA devices in order to build an accelerated spiking neural
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The Department of Electrical & Computer Engineering (ECE) at The University of Alabama is recruiting motivated PhD students to join our cutting-edge research program.Qualified applicants can
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position within a Research Infrastructure? No Offer Description The Embedded and Networked Things (ENT-Lab) Group at the University of Trento, Italy, is currently seeking a PhD candidate to join the MSCA
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 2 months ago
arithmetic cores for FPGAs). The team hosts 6 faculty, 6 PhD students, 3 postdocs, 2 engineer, and multiple research interns. Additional information can be found on team website: https://team.inria.fr/emeraude
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longer sustainable. This project pioneers a new paradigm: we design smart, low-power digital AI co-processors that learn and correct the imperfections of their analog counterparts in real-time. As a PhD
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Researcher (R2) Positions PhD Positions Country Austria Application Deadline 15 Oct 2025 - 23:55 (Europe/Brussels) Type of Contract Temporary Job Status Part-time Offer Starting Date 1 Nov 2025 Is the job
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platform. About the position We are looking for a motivated PhD's degree holder for a full-time position, to carry out high-quality research and development in the optical quantum communication group
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance