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the field of low-latency wireless embedded systems. The research of this PhD position will be conducted within the IDLab-UAntwerp research group. The successful candidate will join a diverse and international
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candidate for a full-time PhD position in Advanced Physical Security of Embedded Systems. You will become part of an active and interdisciplinary cybersecurity research environment and have the opportunity
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that mucus turnover defeats within hours. This project addresses this challenge by creating an orally delivered, bioresorbable retentive structure that incorporates a mixture of embedded systems on flexible
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 5 days ago
precise control cache contents in multi-core architectures for embedded real-time systems. The main idea is to take advantage of the content lifespan of cache blocks, in order to: prevent the hardware
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Reference Number BAP-2026-500 Is the Job related to staff position within a Research Infrastructure? No Offer Description Modern embedded AI systems rely on Deep Neural Networks (DNNs) running on resource
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Job related to staff position within a Research Infrastructure? No Offer Description Techniques based on formal methods for the verification and validation of embedded and safety-critical systems
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-performance Olympic programme ahead of Los Angeles 2028 and beyond. Working as an embedded researcher within GB Taekwondo, you will explore current nutrition practice and the views of male and female athletes
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Are you interested in shaping the future of intelligent and secure computing systems where artificial intelligence meets reliable embedded hardware? We are looking for a motivated PhD candidate, as
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rely on 3D Mechatronic Integrated Devices (3D-MID) to reduce wiring, weight and bulkiness. More advanced 3D-MID components also contain embedded active devices such as multi-modal sensors and
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices