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the power of AI/ML and software-defined networking (SDN), and distributed learning methodologies, the research will focus on creating self-configuring, self-optimizing, and self-healing mechanisms for real
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competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT4 on Reliability and Trustworthiness
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. Funding This is a self-funded PhD. Find out more about fees. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and
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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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equipment, and have access to valuable industry data. The student will benefit from opportunities to present at leading international conferences. Additional training in software-defined radio, hardware-in
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must meet the conditions defined for admission to a PhD programme at NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree or a cand.med.vet
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that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3
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interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3 on representation
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innovation network, the PhD stipends will be closely linked to fellow researchers at other Danish universities through both academic and social events. You will have access to state-of-the-art laboratory
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individual processes to entire manufacturing systems. The PhD projects will all focus on factory and line level, where three research topics are defined: 1) Conceptual design principles and methods