18 network-coding PhD positions at NTNU Norwegian University of Science and Technology
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the design of a scalable, interoperable, and resilient quantum internet architecture and protocol stack for real-world operation in hybrid quantum–classical networks across intra- and inter-domain settings
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application process here. About the position The Department of Information Security and Communication Technology invites applications for a fully funded PhD position on AI-driven network operations for cloud
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relevant topic in machine learning, embedded systems, and edge intelligence Knowledge of accelerator simulators Strong knowledge in deep learning, particularly dynamic neural networks Experience with
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in national and international activities such as conferences, seminars and workshops Follow the activities of and potential to build network in the national and international industry Be prepared
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on the problem of making distributed machine learning robust to network outages and computational bottlenecks. The work is part of the Norwegian national AI centre SURE-AI, and the PhD student will
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interconnected Internet-of-Energy (IoE) ecosystems. In this context, the MSCA Doctoral Network project SAILING (https://Secure AI and Digital Twin Empowered Smart Internet-of-Energy ) aims to establish a
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and abroad. A professional and inclusive work environment . Favourable terms in the Norwegian Public Service Pension Fund Employee benefits at NTNU Salary and conditions As a researcher (code 1109) you
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contribute to one or more of SURE-AI’s work packages and innovation clusters, engage in collaboration across the SURE-AI network, and participate in all relevant center activities. Required selection criteria
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European MSCA Doctoral Network UNVEIL , where you will work together with 11 other PhD candidates employed at different leading universities, research institutes, companies and museums throughout Europe
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academic environment CELECT facilities, industrial network, a joint PhD environment and access to PhD school Inrescos Excellent research infrastructure (Experiments and modelling) Industry-as-laboratory