Our department is looking for a research assistant for the AI4Open6GNet project. The project is funded as part of an international collaboration between Germany and South Africa and aims to develop AI-based mechanisms for sustainable, resilient, and inclusive 5G/6G networks. The focus is on the expansion and integration of open-source mobile communication technologies, as well as the use of artificial intelligence for the automation, optimization, and energy-efficient design of modern mobile networks.
The project connects research and development activities in Germany and South Africa and contributes to open, interoperable, and future-proof network architectures that support both technological sovereignty and societal priorities such as sustainability, digital inclusion, and robust communication infrastructures.

Open-source mobile communications, AI-driven network automation, and research. The research assistant is responsible for carrying out the research activities of the Technical University of Berlin (TUB), which focus on expanding the Open-Source www.Open6GNet.org initiative, including:

• Investigating the state of the art in virtualized open-source (O)RAN, CORE, and SMO components
• Installing and integrating the available RAN, CORE, and SMO components in various meaningful combinations within scalable edge/cloud infrastructures and creating reproducible blueprints for private end-to-end (E2E) 5G/6G testbeds
• Adapting and extending these E2E networks with a view to dedicated end devices and applications to create blueprints for various 5G/6G applications, e.g., security services (MCX), agriculture, eHealth, etc.
• Integrating AI functions/algorithms for network automation (planning, installation, operation, and runtime optimization) with a view to intent-based management
• Implementation of practical validation tools based on third-party software
• Validation of the newly developed concepts and mechanisms in Germany and South Africa
• Presentation of project results at international and national conferences

A doctoral thesis resulting from this work is possible.

• Successfully completed univrsity degree (Master, Diplom or equivalent) in Computer Science or equivalent
• Solid foundations of distributed computing and networking)
• In-depth knowledge of 5G/6G architectures, familiarity with 3GPP standards, ORAN architecture, and SMO concepts
• Fundamentals of machine learning (e.g., reinforcement learning, anomaly detection), experience with AI frameworks (PyTorch, TensorFlow, scikit-learn), understanding of intent-based networking, ability to integrate AI algorithms into network automation chains
• Experience with telemetry stacks (Prometheus, Grafana, Kafka)
• Experience with at least one open-source mobile network stack (Open5GS, srsRAN, OAI, free5GC), ability to integrate RAN and core components
• Experience with containerization (Docker), Kubernetes-based orchestration
• Experience with Ansible or Terraform for Infrastructure-as-Code
• Very good knowledge of Linux systems
• Good knowledge of software networks and communication systems
• Practical experience in prototype development
• Debugging network and software issues, using analysis tools (Wireshark, tcpdump, iperf)
• Proficiency in C/C++, Go, and Python
• Ability to write technical documentation desirable
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills
• Experience with MCX services (Mission Critical Services) and Session‑Initiation‑Protocol‑based communication architectures desirable
• Knowledge in eHealth, agriculture, smart city, or other 5G/6G use cases desirable
• Experience with international testbeds (e.g., Slices RI) desirable
• Experience with machine learning (PyTorch, TensorFlow, scikit‑learn) desirable
• Knowledge of intent‑based networking desirable
• Basic knowledge of cloud infrastructures (OpenStack or comparable) desirable
• Experience with third‑party software for network validation desirable
• Experience in BMBF (German Federal Ministry of Education and Research) or EU research projects desirable

You will work in a dynamic, innovation-driven environment in close collaboration with leading researchers in the field of software-defined networks, as well as national and international research and development institutions. At the Technical University of Berlin, you can expect an excellent academic environment at a renowned, globally connected technical university. We offer an open, respectful communication environment, diverse opportunities for creative input, and flexible work schedules to help you achieve an optimal work-life balance.

Please send your application with the reference number and the usual documents (one file max. 5 MB) only via email to office@av.tu-berlin.de.

Please combine all documents into a single PDF file named Bewerbung_Kennziffer_Firstname_Lastname.

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.