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of the central challenges on the path toward large-scale quantum computing. In this PhD project, you will investigate how machine learning can enable faster, more scalable QEC decoding. The goal is to develop new
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clusters with low power consumption and ultra-low and deterministic latency. The focus of the PhD activity is on demonstrating disruptive new network architectures for AI compute clusters utilizing optical
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the opportunity to work in a world-renowned research institute alongside faculty, software engineers, PhD students, and PostDocs on the development of cutting-edge AI-ready/agentic infrastructure and data systems
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projects. Digital VLSI and AI Hardware Systems Key research areas: ASIC/FPGA design flows; AI/edge accelerators; hardware–software co-design; modern SoC architectures; verification and architecture
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projects. Digital VLSI and AI Hardware Systems Key research areas: ASIC/FPGA design flows; AI/edge accelerators; hardware–software co-design; modern SoC architectures; verification and architecture
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are within two years of completing their PhD. The contract is a two-year contract, extendable by one year. Are you as excited about quantum technology and its future applications as we are? We are seeking a
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 17 Sep 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Hours Per Week 37.5
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between humanities and social science researchers, cultural heritage professionals, and software developers. You will assist with making and refining 3D scholarly models as well as help ensure
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Multiple Tenure-Track Assistant Professor Positions in Microelectronics, Circuits and Systems Design
laboratory modules; mixed-signal design projects. Digital VLSI and AI Hardware Systems Key research areas: ASIC/FPGA design flows; AI/edge accelerators; hardware–software co-design; modern SoC architectures
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Multiple Tenure-Track Assistant Professor Positions in Microelectronics, Circuits and Systems Design
laboratory modules; mixed-signal design projects. Digital VLSI and AI Hardware Systems Key research areas: ASIC/FPGA design flows; AI/edge accelerators; hardware–software co-design; modern SoC architectures