PhD Studentship - Machine Learning for Telecommunication Networks

Loughborough University

Application details:

Start date: 1st October 2018

Closing date: 9th March 2018


Primary supervisor: Dr Mahsa Derakhshani

Secondary supervisor: Professor Sangarapillai Lambotharan

Intro (standard):

Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.

In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Graduate School, including tailored careers advice, to help you succeed in your research and future career.

Find out more:

Project Detail:

We invite applications for a 3-year PhD studentship to study machine learning algorithms aiming to enable emerging applications for telecommunications networks, in the Wolfson School of Mechanical, Electrical and Manufacturing Engineering at Loughborough University. The successful applicant will join the Signal Processing and Networks Research Group, under the supervision of Dr. Mahsa Derakhshani.

This project aims to perform fundamental research in telecommunications networks, focusing on developing algorithms to control and analyse smart and large-scale networks such as smart cities, vehicular networks, and Internet-of-Things (IoT). Learning-based algorithms can enable the system to understand the network dynamism, forecast based on the context information, and proactively manage resources to achieve the network-level and user-level performance targets such as Quality-of-Service (QoS) requirements, privacy and security constraints, and seamless mobility experience. This project also involves theory building to study the scalability, performance and stability of the learning-based algorithms in large-scale networks with unknowns and imperfections.

Find out more:

Applicants seeking additional information are invited to contact Dr Mahsa Derakhshani (

Entry requirements:

Applicants should have a 1st class or high 2:1 honours (or equivalent) degree in Electronic Engineering, Computer Science, or a closely related discipline. An MSc with Distinction is desirable. Strong analytical skills, mathematical background, and experience in MATLAB programming are required. Knowledge of wireless communications, optimization techniques, and machine learning algorithms is desirable.

Funding information:

Please note that these studentships will be awarded on a competitive basis to applicants who have applied to this project and/or the following 30 projects that have been prioritised for funding; job advert ref: WS01 – WS30

If awarded, each 3 year studentship will provide a tax-free stipend of £14,786 p.a ( provisional), plus tuition fees at the UK/EU rate (currently £4,262 p.a). While we welcome applications from non EU nationals, please be advised that due to funding restrictions it will only be possible to fund the tuition fees at the international rate and no stipend will be available. Successful candidates will be notified by 30th April 2018.

Contact details:

Name: Dr Mahsa Derakhshani

Email address:

Telephone number: +44 1509 227193

How to apply:

All applications should be made online at Under programme name, select Electronic & Electrical Engineering

Please quote reference number: WS19

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Midlands of England