PhD Studentship in Energy Efficient Mobile Networking Systems

The University of Edinburgh

Qualification Type:PhD
Location:Edinburgh
Funding for:UK Students
Funding amount:£19,237 – please see advert
Hours:Full Time
Placed On:7th November 2025
Closes:1st December 2025

One fully funded, full-time PhD position to work with Prof. Mahesh Marina in the Networked Systems Research Group at the School of Informatics, University of Edinburgh.

The broad aim of this project is on a holistic investigation of energy efficiency in next-generation mobile networking systems. In the past decade, on the road to 5G, there has been a transformation in the mobile networking infrastructure. For reduced (CapEx) costs, greater flexibility and faster evolution, mobile core/radio network functions today are largely realised in software over commodity computing hardware in private/public cloud data centres. However, this can come at the cost of performance and slower function processing, which manifests as higher energy consumption and increased operational costs (OpEx) for operators. So, a key focus of this project is on reducing energy consumption contributed by running mobile radio/core network functions in a telecom operator’s virtualised infrastructure (data centre) by leveraging hardware/software accelerators and through energy-aware workload placement. The project overall will involve cutting-edge research towards holistic optimisation of energy efficiency in mobile networks by tackling the above challenges with novel system designs and tailored AI/ML based methods.

Candidate’s profile

  • A First Class Bachelors degree and/or Masters degree in a relevant subject (computer science, engineering, mathematics, or related subject)
  • Proficiency in English (both oral and written)
  • Essential to have strong foundations in computer systems through degree courses or equivalent work experience, particularly in computer networks, operating systems, computer architecture and distributed systems
  • Excellent programming, system building and measurement skills are required
  • Be familiar with, and ideally worked with, cloud computing and virtualisation technologies
  • Familiarity and hands-on experience with machine learning techniques desirable
  • Desirable to have work experience (through internships or similar) in the computing industry

Studentship and eligibility

This EPSRC-BT co-funded Industrial CASE doctoral studentship starting in the academic year 2025/26 covers:

  • Full time PhD tuition fees for a student with a Home fee status (£4,786* per annum)
  • A tax-free stipend of GBP £19,237* per year for 4 years
  • Additional programme costs of £1000 per year

*Rates are for 24/25 as 25/26 rates not yet confirmed

This studentship is suitable only for applicants eligible for “home fee” status.

Find out more and apply.

Closing date: 1 December 2025