RIC, and O1/O2/E2 interfaces. Deep knowledge of 5G SA core and RAN architecture (gNodeB, AMF, SMF, UPF components). Solid understanding of Massive MIMO, beamforming, and dynamic spectrum sharing (DSS). Strong grounding in RF principles, propagation models, and coverage/capacity planning. Knowledge of cloud-native technologies, including Kubernetes, Docker, andMore ❯
RIC, and O1/O2/E2 interfaces. Deep knowledge of 5G SA core and RAN architecture (gNodeB, AMF, SMF, UPF components). Solid understanding of Massive MIMO, beamforming, and dynamic spectrum sharing (DSS). Strong grounding in RF principles, propagation models, and coverage/capacity planning. Knowledge of cloud-native technologies, including Kubernetes, Docker, andMore ❯
RIC, and O1/O2/E2 interfaces. Deep knowledge of 5G SA core and RAN architecture (gNodeB, AMF, SMF, UPF components). Solid understanding of Massive MIMO, beamforming, and dynamic spectrum sharing (DSS). Strong grounding in RF principles, propagation models, and coverage/capacity planning. Knowledge of cloud-native technologies, including Kubernetes, Docker, andMore ❯
RIC, and O1/O2/E2 interfaces. Deep knowledge of 5G SA core and RAN architecture (gNodeB, AMF, SMF, UPF components). Solid understanding of Massive MIMO, beamforming, and dynamic spectrum sharing (DSS). Strong grounding in RF principles, propagation models, and coverage/capacity planning. Knowledge of cloud-native technologies, including Kubernetes, Docker, andMore ❯
SA, Open RAN, and cloud-native RAN architecture Hands-on experience with Kubernetes, Docker, CNFs, and orchestration tools (Linux, Python, Ansible) Strong understanding of RF principles, Massive MIMO, beamforming, and network slicing Proven success in large-scale telecom deployments across multi-vendor environments If you're ready to lead the evolution of wireless networks and work More ❯
SA, Open RAN, and cloud-native RAN architecture Hands-on experience with Kubernetes, Docker, CNFs, and orchestration tools (Linux, Python, Ansible) Strong understanding of RF principles, Massive MIMO, beamforming, and network slicing Proven success in large-scale telecom deployments across multi-vendor environments If you're ready to lead the evolution of wireless networks and work More ❯
SA, Open RAN, and cloud-native RAN architecture Hands-on experience with Kubernetes, Docker, CNFs, and orchestration tools (Linux, Python, Ansible) Strong understanding of RF principles, Massive MIMO, beamforming, and network slicing Proven success in large-scale telecom deployments across multi-vendor environments If you're ready to lead the evolution of wireless networks and work More ❯
virtualisation, and orchestration (Kubernetes, Docker, CNFs). Experience with O-RAN SMO, RIC, and O1/O2/E2 interfaces . Solid knowledge of RF design, Massive MIMO, beamforming, and DSS . Hands-on skills with automation and scripting (Python, Ansible, Bash). Proven leadership in multi-vendor 5G deployments with top-tier vendors (e.g., Rakuten More ❯
international colleagues. Requirement Preferred Qualifications Currently pursuing (or recently completed) a PhD, preferably in Electrical Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM andMIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication andMore ❯
international colleagues. Requirement Preferred Qualifications Currently pursuing (or recently completed) a PhD, preferably in Electrical Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM andMIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication andMore ❯
london (city of london), south east england, united kingdom
MediaTek
international colleagues. Requirement Preferred Qualifications Currently pursuing (or recently completed) a PhD, preferably in Electrical Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM andMIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication andMore ❯
