The University of Manchester is offering a fully funded 3.5-year PhD studentship in Wireless Communication, Signal Processing, and Artificial Intelligence. The studentship is open to candidates eligible for UK Home tuition fee status, with a planned start date of January 2027.

The successful candidate will undertake research on AI-native and sensing-aware wireless systems, focusing on the co-design of communications and sensing technologies. The project aims to integrate modern machine learning, statistical signal processing, and optimization techniques to transform heterogeneous information—including channel and network state, topology, mobility, hardware constraints, and task-level performance metrics—into reliable and efficient wireless communication decisions.

Research activities will span both theoretical development and lightweight hardware prototyping, with opportunities to publish in leading IEEE journals and conferences, as well as prominent AI research venues.

Indicative research directions include:

• Network-level design and multi-node cooperation, including coordination, topology design, and distributed or federated learning.
• Wireless resource allocation and scheduling under multiple performance objectives such as data rate, latency, detection, and localization.
• Reconfigurable and programmable radio environments, including system-level and network-level antenna design.
• Theoretical research with mathematical guarantees, covering convex and non-convex optimization, performance analysis, and machine learning.

The studentship provides full tuition fee coverage and an annual tax-free stipend. The stipend is expected to increase annually in line with UKRI rates. Applications are encouraged as early as possible, as the advertisement may close once the position has been filled.

[Eligibility Criteria]

• Applicants should hold, or expect to obtain before commencement, a Master’s degree (or international equivalent) in a relevant science or engineering discipline.
• Candidates must be eligible to pay UK Home tuition fees.
• Demonstrated research potential is highly desirable, including evidence such as peer-reviewed publications in high-quality journals or conferences where applicable.

[Required expertise/skills]

• Strong programming skills in optimization and/or machine learning.
• Experience with Python, MATLAB, or C++.
• Familiarity with machine learning frameworks such as PyTorch or TensorFlow.
• Knowledge of wireless communications and signal processing.
• Experience with software-defined radio (SDR) or GPU prototyping is advantageous.
• Strong analytical, research, and communication skills.

[Salary details – if available]

• Fully funded studentship.
• Annual tax-free stipend of £21,805 (UKRI rate for 2026/27), with expected annual increases.
• Full Home tuition fees covered.

[Application Deadline – if available]
2 September 2026. Applications are encouraged early, as the position may close once filled.

Application Link 

Dr Kaitao Meng
Email: kaitao.meng@manchester.ac.uk