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                Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable 
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                funded PhD position invites applications from candidates interested in the intersection of computational design, robotic fabrication, and environmentally performative architecture. The research will 
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                the intersection of computational design, robotic fabrication, and environmentally performative architecture. The research will investigate how 3D printed clay systems—columns, claddings, and related architectural 
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                technology for the forthcoming generation of highly energy-efficient computing systems. FeFETs are programmable, non-volatile silicon devices that enable innovative architectures to efficiently execute complex 
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                system architecture can be extracted and represented in a language-agnostic way, relying in the capabilities of program analysis,generative AI, and advanced visualisation techniques. We require candidates 
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                disciplines, including architectural design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities 
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                technology for the forthcoming generation of highly energy-efficient computing systems. FeFETs are programmable, non-volatile silicon devices that enable innovative architectures to efficiently execute complex 
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                20 Sep 2025 Job Information Organisation/Company University of Groningen Research Field Computer science » Computer architecture Researcher Profile First Stage Researcher (R1) Country Netherlands 
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                10 Oct 2025 Job Information Organisation/Company Wageningen University & Research Research Field Architecture » Landscape architecture Researcher Profile First Stage Researcher (R1) Country 
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                Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs