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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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, particularly in computer networks, operating systems, computer architecture and distributed systems Excellent programming, system building and measurement skills are required Be familiar with, and ideally worked
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to WAN and inter-domain networking, Excellent command of foundational and applied AI technology, from neural networks, distributed reinforcement learning to agentic AI and recent developments in
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): Network-level design and multi-node cooperation (coordination, topology design, distributed/federated learning, etc.) Wireless resource allocation and scheduling under multi-objective KPIs (rate, latency
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optimization of complex systems, intelligent data and information systems, as well as networks, distributed systems, and security. LIMOS stands out for its interdisciplinary approach, combining theoretical
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to develop innovative and breakthrough research in the field of multicore fibre (MCF) technology. MATCH (Multicore Fiber - Applications and Technologies - Match) is a Marie Sklodowska-Curie doctoral network
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medicine. The laboratory benefits from a large network of national and international collaborations and access to cutting-edge technological platforms, including advanced microscopy, high-throughput
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the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network project ANT. The objective of Doctoral Networks is to implement doctoral programs by partnerships of organizations from different sectors across
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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research school on secure distributed computing (SeDiC) is proposed. SeDiC aims to tackle the challenges of exchanging and computing data across a network of interconnected systems. It addresses scalability