At a Glance
- Tasks: Conduct groundbreaking research on AI-native 6G networks and develop innovative solutions.
- Company: Join Queen Mary University of London, a leader in electronic engineering and computer science.
- Benefits: Fully funded PhD with a stipend of approximately £21,874 per year.
- Other info: Collaborate on cutting-edge projects and publish findings in leading journals.
- Why this job: Shape the future of telecommunications and AI while working with top academics.
- Qualifications: Bachelor’s or Master’s in relevant fields; strong research potential and programming skills required.
The predicted salary is between 21874 - 21874 £ per year.
Job Title
Fully Funded Ph D Researcher – AI‑Native 6G Networks | Queen Mary University of London (QMUL) | London, United Kingdom
Recruiting Company
Queen Mary University of London (QMUL) – School of Electronic Engineering and Computer Science
- Job Location
- London, United Kingdom
- Job Type
- Full-Time | Fully Funded Ph D Studentship | Research Position
- Application Method
- Contact: a. masaracchia@qmul. ac. uk
- Funding Information
- Funding: Full Tuition Fees (Home Rate - UK Residents)
- Annual Stipend: Approximately £21,874 per year
- Duration: 3 Years
- Start Date: April 2027
- Application Deadline: Contact the Supervisor for Further Details
- Research Area: Artificial Intelligence, 6G Networks, Wireless Communications
- Application Information: Online
- Position Summary
Queen Mary University of London is seeking a highly motivated Ph D candidate to join a cutting‑edge research project focused on AI‑Native Cross‑Layer Resource Allocation for Intelligent 6G Networks.
This fully funded doctoral opportunity offers the chance to work at the forefront of artificial intelligence, wireless communications, and next‑generation mobile network technologies that will shape the future of intelligent and autonomous 6G systems.
Detailed Job Description
This Ph D studentship will explore how AI-native network architectures and Hierarchical Multi-Agent Reinforcement Learning (HMARL) can transform the management and optimization of future 6G Radio Access Networks.
The successful candidate will conduct advanced research into predictive network intelligence, cross‑layer optimization, and data‑centric AI techniques to improve network efficiency, reliability, and user experience.
Working within the renowned School of Electronic Engineering and Computer Science at QMUL, the researcher will collaborate with leading academics and contribute to innovative solutions addressing some of the most challenging problems in wireless communications.
The project combines theoretical research, algorithm development, simulation, and performance analysis, providing an excellent platform for candidates interested in pursuing careers in academia, telecommunications research, AI, or advanced wireless systems engineering.
Key Responsibilities
- Conduct original doctoral research in AI-native wireless network architectures and intelligent 6G systems.
- Design and develop advanced machine learning and reinforcement learning algorithms for radio resource management.
- Investigate Hierarchical Multi-Agent Reinforcement Learning (HMARL) approaches for autonomous RAN optimization.
- Develop predictive traffic forecasting and mobility modeling techniques for next‑generation wireless networks.
- Perform cross‑layer optimization research across radio, network, and service layers.
- Design simulation frameworks and conduct performance evaluations of proposed 6G solutions.
- Analyze large‑scale wireless network datasets to support data‑driven decision‑making and optimization.
- Publish research findings in leading international journals and conferences.
- Present research outcomes at academic, industry, and scientific forums.
- Collaborate with academic supervisors and research teams on cutting‑edge telecommunications and AI initiatives.
- Required Qualifications & Skills
- Bachelor’s and/or Master’s degree in Telecommunications Engineering, Electronic Engineering, Computer Science, Artificial Intelligence, Data Science, Mathematics, or a closely related discipline.
- Strong academic background with demonstrated potential for high-quality research.
- Knowledge of wireless communications, mobile networks, or Radio Access Network (RAN) technologies.
- Understanding of machine learning, artificial intelligence, or reinforcement learning concepts.
- Programming experience in languages such as Python, MATLAB, C++, or similar.
- Strong analytical, mathematical, and problem‑solving abilities.
- Ability to conduct independent research and manage long‑term research objectives.
- Excellent written and verbal communication skills.
- Strong motivation to pursue a Ph D in advanced telecommunications and AI‑driven network systems.
- Eligibility for Home Rate tuition funding as specified by the studentship requirements.
- Nice‑to‑Have Skills
- Experience with reinforcement learning or multi‑agent learning frameworks.
- Knowledge of 5G Advanced, Open RAN, or emerging 6G technologies.
- Familiarity with AI‑driven radio resource management techniques.
- Experience with network simulation tools and wireless performance evaluation.
- Prior research experience resulting in publications, dissertations, or research projects.
- Understanding of optimization theory, stochastic processes, or network modeling.
- Recruitment Pro Tip
For a competitive Ph D application, demonstrate not only strong academic performance but also a clear research interest in AI, machine learning, and wireless communications.
Highlight any research projects, publications, dissertations, programming experience, or practical work involving telecommunications, reinforcement learning, network optimization, or data analytics, and clearly explain how your interests align with the vision of intelligent AI‑native 6G networks.
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Fully Funded PhD Researcher – AI-Native 6G Networks | Queen Mary University of London (QMUL) | London, United Kingdom employer: Queen Mary University of London (QMUL) – School of Electronic Engineering and Computer Science
Queen Mary University of London (QMUL) is an exceptional employer, offering a fully funded PhD studentship that allows researchers to engage in groundbreaking work at the intersection of artificial intelligence and next-generation wireless communications. Located in the vibrant city of London, QMUL fosters a collaborative and innovative work culture, providing ample opportunities for professional growth and development while contributing to pioneering research that shapes the future of technology.
Contact Details:
Queen Mary University of London (QMUL) – School of Electronic Engineering and Computer Science Recruitment Team
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