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for edge/cloud continuum, real-time KPI/KVI monitoring, automated network and application adaptation workflows, integration with network exposure APIs and RAN/edge intelligence layers. Contribute
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Framework Programme? Horizon Europe - EIC Is the Job related to staff position within a Research Infrastructure? No Offer Description Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud company
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Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable autonomous and efficient network/service management. The PhD candidate will investigate innovative
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and manage high‑throughput workloads on HPC or cloud infrastructure, including parallelization, traceability, reporting and workflow orchestration through Nextflow. Collaborate with data/AI engineers
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for next-generation (6G) communication systems. The project focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable
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as more is learned about the underlying hardware. The resulting framework will support on device intelligence without cloud connectivity, ensuring privacy, robustness, and predictable performance in
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). Develop robust, reproducible and reusable Python code for model training, inference, and large‑scale computational experiments. Run and manage high‑throughput workloads on HPC or cloud infrastructure
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service delivery across heterogeneous infrastructures, including terrestrial and non-terrestrial networks, cloud-edge environments, and vertical industry domains. The PhD candidate will investigate
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and