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-native networks or financial services, AI/ML that is not secure, robust, verifiable, or privacy-preserving can lead to safety risks, regulatory violations, and significant reputational damage. By making AI
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application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer
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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
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experimentally verified results is a necessary: - Autonomy with collaborative intelligence - Distributed task and motion planning - Predictive collaboration with heterogeneous teaming - Multi-agent navigation in
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researcher position will focus on the following key areas, where a proof of previous work with experimentally verified results is a necessary: - Autonomy with collaborative intelligence - Distributed task and
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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This PhD project focuses on advancing network security in the emerging Web3 ecosystem. As decentralized applications built on blockchain and distributed ledger technologies become more widespread
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, distributed across 15 units at Uppsala University and the Swedish University of Agricultural Sciences (SLU). The central hub of this network is Navet, located at the Biomedical Centre (BMC), which serves as a
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build the sustainable companies and societies of the future. Pervasive and Mobile Computing (PMC) research subject addresses fundamental challenges in distributed systems and mobile networks, enabling
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build the sustainable companies and societies of the future. Pervasive and Mobile Computing (PMC) research subject addresses fundamental challenges in distributed systems and mobile networks, enabling