PhD Projects

Postgraduate Studentships

Postgraduate Studentships

We have a number of PhD studentships available for applicants in the UK and EU countries who wish to undertake full-time research at Queen's. These 3 year and 4 year PhD studentships, potentially funded by the Department for Employment and Learning (DEL) or Engineering and Physical Sciences Research Council commence on 1 October 2019.


Academic Requirements

A minimum 2.1 honours degree or equivalent in Electrical and Electronic Engineering, Computer Science or relevant degree is required.



More information on funding of a PhD can be found at 

In some instances, conditions on awards with eligibility for both fees and maintenance (£15,038 in 2019/20) depends on the applicants being either an ordinary UK resident or those EU residents who have lived permanently in the UK for the 3 years immediately preceding the start of the studentship. Non UK residents who hold EU residency may also apply but if successful may receive fees only.



2019 PhD Projects



The table below shows all of our current opportunities in the area of Cyber Security.

Applicants should apply electronically through the Queen’s online application portal at:



Proposed Project Title and Purpose


Applying Deep Learning to Enhance Physical Unclonable Functions

Prof Máire O'Neill

Deep Evidential Alert Correlation for Total Network Defence

 Dr. Paul Miller

Scalable Forensics for Future Networks

Dr. Sandra Scott-Hayward




Software Vulnerability Detection and Remediation 

 Privacy-aware cybercrime tracking                                             

Deep Pose Estimation and Activty Recognition in Social Media Videos 

 Edge-based solution to IoT attacks                                                         

Unifying Static and Dynamic Malware Analysis 

 Practical and Post-Quantum IoT Security                                            

 Defending ML-based Network Security Systems from Adversarial Attacks

 Breaking Security Devices                 

 Adversarial deep learning for  malware analysis: deception and countermeasures

Eco-friendly Distributed Ledger Technologies (DLTs) for the future

 High-speed Post Quantum Cryptography

Secure Information Centric Networking

Post-Quantum Anonymous Credential






Proposed Project Title and Purpose


Understanding the brain and its diseases: building an ontology for the clinical neurosciences.  Dr Barry Devereux
Meaningful Object Processing in Mind and Machine Dr Barry Devereux & Paul Miller
Predicitive analytics in an ICU by processing streams of physiological data in real-time  Dr Charles J Gillan 
Energy-Efficient, Robust and Secure Data Storage Using Data Mining and Analysis   Dr. Georgios Karakonstantis
Energy-Quality Scalable Processors under Dynamically Varying Operating Conditions  Dr. Georgios Karakonstantis
Implementation of a smart energy-efficient data analysis system for food safety and authenticity  Dr. Georgios Karakonstantis
On Analysing Urban Mobility Data for Smart Cities  Dr Cheng Long

Spatio-Temporal Analytics on Sports Data

 Dr Ivor Spence

Crowd analysis using Deep Neural Networks

 Dr. Jesus Martinez del Rincon   


 Dr. Jesus Martinez del Rincon  

Cyber-Physical AI on Embedded/Edge/Cloud Architectures.

 Dr. J. McAllister

FPGA-based Artificial Intelligence

 Dr. J. McAllister

FPGA-based Sparse Graph Analytics

 Dr. J. McAllister

Quantum Computer Architecture

 Dr. J. McAllister

Deep relational reinforcement learning

 Dr. Vien Ngo

Human-robot collaboration as end-to-end learning 

 Dr. Vien Ngo

Meta Learning for Deep Reinforcement Learning and Robotics

 Dr. Vien Ngo

Planning and Representation Learning under Uncertainty for Motor Primitives and Robotics

 Dr. Vien Ngo

The Science of Virality in Social Media

 Dr Deepak Padmanabhan

Gentleman AI

 Dr Deepak Padmanabhan

Striking Features for Similarity Search

 Dr Deepak Padmanabhan

Making sense of cancer data 

 Prof. Neil M. Robertson

Durable concurrent data structures for non-volatile main memory

 Dr Hans Vandierendonck 

High performance graph analytics 

 Dr Hans Vandierendonck 

LEEWAY – Lean Efficient Edge-based WorkloAd DeploYment on the Internet

 Dr Blesson Varghese

RAMEN: RApid Migration at the Edge of the Network

 Dr Blesson Varghese

Blockchain based trust mechanisms for future clouds

Dr Blesson Varghese

High performance software for analysis of mass spectrometry data applied to challenges in Global Food Security

  Dr Charles J Gillan 


Key ECIT Contacts

Meet our pioneers