About the Project
The next-generation, i.e., the Fifth Generation (5G), mobile networks are currently being developed worldwide and pilot 5G systems are planned to be deployed at around 2020 in Europe. It is therefore high time for 5G stakeholders from industry, academia and beyond to investigate fundamental enablers to achieve the 5G vision of a globally fully connected community. This PhD programme is aligned with a major, multi-million-pound European 5G project SELFNET (https://selfnet-5g.eu/), technically coordinated by Prof. Qi Wang and Prof. Jose M. Alcaraz Calero at UWS, who will also be the lead supervisors of this PhD programme. Furthermore, this project will be in collaboration with NATS (http://www.nats.aero/), UK’s leading provider of air traffic control services. The programme is funded by the prestigious UWS Vice Principal (VP) Fund for strategically important projects.
The focus of this project is to research and develop enabling technologies and novel techniques to support demanding, high-quality video applications such as Augmented Virtual Reality (VR) over 5G and other challenging networking environments. Potential example use cases may include Immersive Campus for the higher education sector, Mobile Health for the healthcare sector, and Tele-presence, Mobile/Remote Farming for ultra-precision in agriculture sector, Smart Surveillance and Remote Collaborative Operations for mission-critical industrial operations. This project will contribute to realising this vision.
The PhD student will join a team of experienced researchers at UWS, and have the opportunity to collaborate with external stakeholders including NATS, European 5G industry or research partners such as those in the SELFNET Consortium and US academic advisors. Applicants should hold a minimum 2:1 degree or a master’s degree in computer science or other relevant disciplines, or have equivalent industry experiences. It is essential that the applicant has good skills in computer programming and good knowledge in one or more of the following areas: computer networks, video signal processing or transmission, artificial intelligence, machine learning, software engineering, mathematical modelling, and/or telecommunications.
Informal enquiries may be addressed to either [Email Address Removed], [Email Address Removed], or [Email Address Removed].
Funding Notes
Successful candidates will receive an annual stipend (currently £14,296) per annum for three years and payment of tuition fees (current value £4052). Applicants are advised that funding will be considered as part of a competitive round and there is no guarantee that it will be awarded. Successful applicants will be expected to contribute up to 6 hours/week to UWS’ academic related activities.
Studentships are open to Home/EU candidates with a first degree in a relevant discipline. Non-EU students can apply, but will not receive the stipend and will be required to pay fees.
References
UWS is an inspiring, vibrant place to study with a growing research community; an important aspect of which is its outstanding and committed research students.
How to apply:
Postgraduate Degree by Research Applications should be completed online at
http://www.uws.ac.uk/research/graduate-school/prospective-students/
Applications without all relevant documents will not be considered. Please quote the Project Reference Number.
Continue with Facebook
