Requirements: English
Company: IIT-CNR
Region: Pisa , Tuscany
A fully funded 3-year Ph.D. position in NetworkIntelligence in 6G networks within the Italian National PhDProgram in Artificial Intelligence is sponsored by the UbiquitousInternet (UI) research group of IIT-CNR. We are looking for ahighly motivated PhD candidate with a strong academic background tojoin our research team and work on this Ph.D. topic under oursupervision.This scouting notice aims to raise awareness of theupcoming Ph.D. admission call that will be officially opened by theUniversity of Pisa in June.Interested candidates should send thefollowing documents in a single PDF file:A detailed CVA list ofpublications (if any), or a summary of relevant researchexperienceTranscripts (Bachelors and Masters degrees)Start of thePh.D. course: November 1st, 2025. Workplace: Pisa, ItalyMoreinfromation about the PhD program and the research group:https://ui.iit.cnr.it/en/BackgroundOne of the primary objectives offuture 6G networks is to enable AI-driven intelligence across alllayers. AI will be both a service and a native feature within the6G communication system, making 6G an end-to-end (E2E) AI-poweredecosystem that supports intelligent services and applications. Asnetwork complexity escalates with the prolifeartion of diversedevices, incrising data volumes, and heterogenous protocols, andthe requirements of emerging applications become more demanding, 6Gmust leverage E2E AI and ML models to improve network optimizationand automate various aspects of network management. This willenable predictive analysis, proactive network management, anddynamic performance alignment to meet diverse E2E demands. TopicdescriptionThe research challenges addressed by this PhD include,but are not limited to::the desig of new solutions that leveragerecent breakthroughs in generative artificial intelligence (GAI) tosupport closed-loop network intelligence across the entire E2Enetwork architecture, effectively managing conflicts among multipledecision-making agents operating in different network domains orsegments; the development of robust mechanisms for interpretingnetwork intelligence decisions and outcomes, utilizing explainableAI (XAI) models to enhance transparency and accountablity.CandidateprofileThe candidate must have (or be about to obtain) a Mastersdegree (or equivalent) in Computer Science, Computer Engineering,Telecommunications Engineering, or a closely related field. Anexcellent academic record is required, with outstanding marks insubjects such as networking, optimization, and artificialintelligence.Technical SkillsThe following skills are an advantagefor the candidate:Experience or familiarity with ML/AI techniquesapplied to networking. Knowledge of general networking principlesand mobile network architectureProficiency in programming (Python,C++, or similar languages).