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                22 Oct 2025 Job Information Organisation/Company UNIVERSIDAD POLITECNICA DE MADRID Department HRS4R Research Field Architecture » Other Researcher Profile First Stage Researcher (R1) Positions 
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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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                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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                should have the competencies of R3 category. Required qualification/skills/experience: - PhD degree in Electrical and Electronic Engineering or a related discipline (e.g., Telecommunications, Computer 
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                Innovative Computer Architecture group and become part of the CogniGron research centre as well as the NL-ECO project. Where to apply Website https://www.academictransfer.com/en/jobs/354943/phd-in-simulators 
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                institution and in a relevant field for this position (e.g., in electrical engineering, physics or computer science). The selected candidate will be enrolled in a PhD degree program at Iscte.Planned secondment 
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                14 Nov 2025 - 09:44 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff 
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                -time basis for a duration of up to 3 years, with the possibility of part-time work. The position includes the opportunity to pursue a doctorate (PhD) at TU Clausthal. With these positions, we invite YOU 
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                papers Contributing to educational events, such as courses and hackathons Your Profile: Excellent Master or PhD degree in Computer Science, Mathematics, Physics, or similar fields Good knowledge of AI and 
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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