Research course

Communications (EPSRC Centre for Doctoral Training)

University of Bristol · Faculty of Engineering

Entry requirements

An upper second-class honours degree (or international equivalent) in electrical and electronic engineering, mathematics, computer science, physics or similar numerate discipline.

Months of entry


Course content

The UK's only interdisciplinary EPSRC Centre for Doctoral Training in Communications offers graduates of engineering, mathematics and science disciplines a vibrant and stimulating environment in which to undertake research. The centre, funded by EPSRC and industry, addresses the shortage of highly skilled communications engineers by training postgraduates and exposing them to ground-breaking research.

The centre brings together world-leading experts, many of whom also have extensive industrial links. Bristol benefits from a high concentration of communication-related industries in the region. Several of these organisations work closely with the centre and will provide you with industrial training and support, allowing you to obtain skills that will maximise your employability.

The programme will equip you with the necessary skills to work in a wide variety of roles to lead innovative research, future product development and exploitation.

Past PhD topics have included:

  • Adaptive broadcast transmission with end-user metrics;
  • Robust, intelligent video data links;
  • Massive MIMO for high capacity 5G networks;
  • Wireless SDN integration in heterogeneous networks & 5G;
  • Multiple antenna techniques and raptor codes for vehicular communications;
  • Integrated, user-centered health sensing;
  • Leveraging SDN to deliver scalable and energy efficient M2M networks;
  • Optimization of machine-to-machine communication in large scale networks;
  • Target designation and surveillance for live aerial imagery;
  • Stochastic geometry and wireless networks;
  • Next generation conformal antenna arrays for sensors and communications;
  • MU-MIMO techniques;
  • Passive intrusion detection methodology in IoT network systems;
  • Wireless connectivity in autonomous vehicles;
  • Biologically inspired vision systems;
  • SDN (Software Defined Network) Solutions for High-criticality Networks;
  • Efficient power amplifiers for IoT machine-to-machine devices.

Qualification and course duration


full time
48 months

Course contact details

Graduate School of Engineering
+44 (0) 117 954 5395