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PhD Studentship in End-to-End Slice Management in 5G Mobile Networks

The University of Edinburgh

Qualification Type: PhD
Location: Edinburgh
Funding for: UK Students, EU Students
Funding amount: Not Specified
Hours: Full Time
Placed On: 8th November 2018
Closes: 30th November 2018

Topic Description

Research and standardisation for 5G mobile networks is currently underway. A unique aspect of 5G compared to various generations of mobile networks till date is the underlying vision to be the basis for a wide array of services beyond just mobile broadband to include critical and massive machine-to-machine communications, among others. In order to serve such diverse use cases in a flexible and cost-effective manner, 5G network architecture embraces the concept of network slicing that essentially refers to sharing the same physical infrastructure among multiple virtual networks or slices.

5G architectural research till date has largely focused on the necessary systems support to enable 5G network slicing through platforms and frameworks for virtualisation and network softwarisation (via SDN and NFV). Understanding and ensuring service quality, while a natural next step for research on this topic, is largely an uncharted territory. With this in mind, the overall goal of this project is on end-to-end slice management towards service assurance and robustness of coexisting future virtualised 5G services.

Further Details, Eligibility and Application Procedure

This is a 3.5 year fully funded PhD studentship position (fees and stipend included) to start as soon as possible but no later than 1st February 2019. Eligibility requirements include:

  • Only UK/EU based applicants are eligible to apply
  • At least a Bachelor's degree (with Honours) but ideally a Masters degree in Computer Science (or related field) with first class performance
  • Solid background in mobile communications and networks essential, and additionally in network security and applied machine learning preferred
  • Relevant research or industry work experience
  • Possess excellent system building and communication skills, and be able to work well in a team environment

Interested and highly self-motivated candidates meeting the above requirements should contact Dr Mahesh Marina by e-mail in the first instance including detailed CV (with names of at least 2 referees) and previous degree transcripts.

Application Deadline: 30 November 2018 at 5pm (GMT)

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