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Vacancies PhD position on Dependability Driven on Device Learning Algorithms for Embedded Neuromorphic Architectures Key takeaways Edge devices that can learn autonomously while guaranteeing
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solutions. Subject description Cyber-Physical Systems encompass integrated software, electronics hardware, and application architecture within connected devices and distributed systems. The research aims
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industry. Subject description Cyber-Physical Systems encompass integrated software, electronics hardware, and application architecture within connected devices and distributed systems. The research aims
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industry. Subject description Cyber-Physical Systems encompass integrated software, electronics hardware, and application architecture within connected devices and distributed systems. The research aims
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industry. Subject description Cyber-Physical Systems encompass integrated software, electronics hardware, and application architecture within connected devices and distributed systems. The research aims
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urban planning. Research environment This PhD position is part of the Sustainable Urban Water and Environmental Engineering (SUWEE) research area within the Department of Architecture and Civil
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candidate will explore programmable, AI-enhanced networking frameworks designed to meet the evolving demands of Industry 5.0. This includes developing novel architectures that combine Software-Defined
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build the sustainable companies and societies of the future. At the EISLAB division you find Cyber-Physical Systems (CPS) who focuses on integrated software and application architectures with
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#content5-406934 , is participating in cutting-edge CELTIC MECON research project, focusing on network automation in 6G network architectures. The candidate aims to work in the following areas: Machine
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machine learning, with the goal of revealing how genome architecture shapes physiology, ecology, and evolution. Unlock hidden biological patterns while developing key computational and academic skills. Your