|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||£16,062 Stipend per annum|
|Placed On:||4th July 2022|
|Closes:||4th October 2022|
Qualification: Doctor of Philosophy in Engineering (PhD)
Start date: 9th January 2023
Funding for: UK Students for 3.5 years
Supervisor: Professor Gan Zheng
Machine Learning for 6G Communications Networks: Future 6G wireless networks need to address the challenge of fast and dynamic resource allocation to satisfy the demand of massive connections, ultra-low latency and ultra-high high reliability and capacity in mobile communications networks and Internet-of-Things networks. However, existing resource allocation algorithms are too complex and slow, and do not fit for purpose.
This project will develop a purpose-built deep learning architecture and new algorithms for 1) real-time optimal resource allocation with a guarantee on individual and overall system performance; 2) tackling uncertainties in the radio environment including channel variation, dynamic spectrum sharing, network congestion, user mobility and activities; 3) proactive resource optimization by exploiting the context information and predicting the future network environment. Advanced techniques such as graph neural networks, meta-learning, neuromorphic computing and quantum machine learning will be investigated. The developed new algorithms will enable the 6G networks to have the required cognition and intelligence to rapidly adapt to the dynamic environment and user demand. Through working on this project and joining our renowned Connected Systems Group, you will have the opportunity to work with world-leading experts in signal processing and communications and contribute to the innovation of future wireless networks.
The award will cover the tuition fees, plus a stipend of £16,062 per annum for 3.5 years of full-time study.
Applicants should have or expect to achieve, at least a 2:1 Honors degree (or equivalent) in Electrical Engineering, Computer Science or a related subject. A relevant Master’s degree and/or experience in communications, signal processing and deep learning is welcome.
How to apply:
Candidates should submit an expression of interest by sending a CV and supporting statement outlining their skills and interests in this research area to www.warwick.ac.uk/engpgr/gz/appcv/. If this initial application is successful, we will invite you to make a formal application for study. All candidates must fulfil the University of Warwick entry criteria and obtain an unconditional offer before commencing enrolment.
The University of Warwick provides an inclusive working and learning environment, recognising and respecting every individual’s differences. We welcome applications from individuals who identify with any of the protected characteristics defined by the Equality Act 2010.
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