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are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources for end-to-end
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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been oriented around high performance computing (HPC) but are increasingly migrating to cloud-based solutions. We are seeking a talented software engineer to bring in this transition. You'll Be Solving
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implementation Knowledge of networking protocols and architectures PhD or equivalent R&D experience in computer science, networks or communications, and/or experience with at least one of the following areas
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/ML frameworks (e.g., TensorFlow, PyTorch, FLOWER). Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and on-premise cloud platform such as VMWARE, and heterogeneous infrastructure