Wireless Communication, Signal Processing, and AI

About the Project

This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal processing, or optimisation to turn heterogeneous knowledge (channel/network state, maps and topology, mobility, hardware constraints, and task-level KPIs) into reliable and efficient decisions. The work spans theory to lightweight on-hardware prototypes, with publications targeted at leading IEEE venues in communications and signal processing, and relevant AI venues.

Indicative directions (choose one or combine):

• Network-level design and multi-node cooperation (coordination, topology design, distributed/federated learning, etc.)
• Wireless resource allocation and scheduling under multi-objective KPIs (rate, latency, detection, localisation, etc.)
• Reconfigurable/programmable radio environments and system/network-level antenna design
• Theory with guarantees (convex/non-convex optimisation, performance analysis, machine learning, etc.)

Eligibility

1. Applicants should have, or expect to achieve, at least a master’s (or international equivalent) in a relevant science or engineering-related discipline.
2. Strong programming ability in optimisation or machine learning (e.g., Python/Matlab/C++; PyTorch/TensorFlow). Experience in signal processing/wireless or SDR/GPU prototyping is a plus.
3. Demonstrated research potential is highly desirable. Evidence may include peer-reviewed publications in top-tier journals (e.g., IEEE Transactions/Letters) and top conferences.

Funding

This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26; subject to annual uplift), and tuition fees will be paid. We expect the stipend to increase each year. The start date is January 2026.

We recommend that you apply early as the advert will be removed once the position has been filled.

Before you apply

We strongly recommend that you contact the supervisor(s) for this project before you apply. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

How to apply

Apply online through our website: https://uom.link/pgr-apply-2425

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

• Final Transcript and certificates of all awarded university level qualifications
• Interim Transcript of any university level qualifications in progress
• CV
• Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it).
• Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
• English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing FSE.doctoralacademy.admissions@manchester.ac.uk.