DC12

This research focuses on developing and implementing intelligent O-RAN intelligent controller (RIC) functionalities for both non-real-time (non-RT) and near-real-time (near-RT) responses. It aims to design and integrate Distributed Applications (dApps) within the non-RT and near-RT RIC, as well as to develop AI-driven solutions for real-time radio access network (RAN) functionalities. The expected outcomes include the implementation of O-RAN functionalities within a testbed platform, incorporating non-RT RIC, near-RT RIC, and dApps. By deploying dApps directly within centralised and distributed units (CUs and DUs), the system will leverage low-level data metrics—such as MAC/PHY-level key performance metrics (KPMs), transmission queues, and beam directionality—to enable AI-driven real-time RAN functions. These functionalities will include beamforming, user scheduling, puncturing, interference management, and modulation management. Additionally, machine learning models will be designed as independent internal applications and deployed within the controllers, allowing their application across various use cases.

1. The candidate must not have been awarded a PhD Degree.
2. A Master’s Degree is required in Electrical Engineering, Computer Science, Telecommunications, or a related field.
3. Candidates must not have resided in Bulgaria for more than 12 months within the three years preceding their employment start date. Additionally, for the remainder of this period, candidates must provide evidence of residing outside Bulgaria.
4. Proficiency in written and spoken English is required and must be formally demonstrated.
5. Expertise in one or more of the following disciplines: Telecommunications, Wireless Networks, Signal Processing, Mathematical Optimization.
6. Proficiency in programming and simulations, especially with Matlab, C, C++ or Python.
7. Familiar with ML frameworks & libraries.
8. Knowledge of scientific work methods and research.