A number of Postgraduate Research Studentships are available within the School of Electronics Electrical Engineering and Computer Science for home and EU students enrolling in 2019.

Further information on potential projects which may be successful for an award can be obtained on our website

 

Please note that not all projects are subject to internal QUB funding.

 

If you have a project of your own, then you should contact a possible supervisor about its viability.

 

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 https://www.qub.ac.uk/sites/graduateschool/PostgraduateFunding/

 

GENERAL INFORMATION

There are 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.

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.

 

Applicants should apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/

 

Applications received after 28^th February 2019 may not be processed in time to receive a DfE award. 

Applicants will be required to undertake an interview. 

 

 

2019/20 Opportunities

Prof. Neil Robertson

• The Unknown Unknowns: Quantifying Uncertainty in Deep Machine Learning

Dr. Ahmad Elkhateb

• Wireless Power Transfer for Charging Electric Vehicles
• Power Electronics Interface for Integrating Wind turbines into the Medium Voltage Distribution System
• A Three-Phase High-Frequency Link Grid Connected Converter

Dr. Amy Liu

• Smart Grid Data Analytics for Security of Energy Supply

Dr. Anna Jurek-Loughrey

• New machine learning approaches to heterogeneous big data analytics in precision medicine
• Machine learning for heterogeneous data integration
• Online Fake News Detection via Diffusion Patterns Analysis
• Novel techniques for automated analysis of social media data

Dr. Barry Devereux

• Understanding the brain and its diseases: building an ontology for the clinical neurosciences
• Meaningful Object Processing in Mind and Machine

Dr. Blesson Varghese

• Blockchain-based Trust Mechanisms for Future Clouds

Dr. Carlos Reano, Dr Blesson Varghese

• GPU Virtualisation in Fog Computing

Dr. David Morales

• Robust High-Dimensional filters for 5G+ wireless communications
• A Random Matrix Inference Framework for Big-Data Analytics

Prof. Dimitrios Nikolopoulos

• Cloud & IoT System Architecture for Digital Manufacturing

Dr. Deepak Padmanabhan

• Health information retrieval
• Exploring the relationship between ‘Fake News’ and Political Orientation using machine-learning
• Emotions and fake news

Dr. Dmitry Zelenchuk

• Advancing mm-wave communications and imaging through novel radiating interfaces

Dr. Des Greer

• Automated Software Refactoring for Concurrency and other Qualities

Dr. E. Garcia-Palacios

• Cognitive Wireless Powered Communication Networks
• Spectrum Access in M2M Communications

Dr. Georgios Karakonstantis

• Energy-Quality Scalable Processors based on Data Mining
• A Smart Data Analysis System for Food Safety based on Pattern Recognition
• Failure Prediction based on Data Mining for Energy-Efficient & Dependable Cloud/Edge Ecosystems
• In-Time and In-Space Sharing of FPGA Resources in Cloud/Edge Ecosystems
• Intelligent Memory Access Pattern Scheduling for Power and Performance Optimization

Dr. Hans Vandierendonck

• Durable Concurrent Data Structures for Non-Volatile Main Memory
• High-Performance Graph Analytics

Dr. Hamza Shakeel

• Development of Highly Sensitive Chemical Detection Platform
• In-situ Characterization of Nanomaterials
• Internet of Things based Calibrated Low Cost Pollution Monitoring Sensor Network
• Optical Readout for MEMS Sensors

Dr. Ivor Spence

• Scaling of OpenCL kernels for multiple accelerators

Dr. Jerry Shen

• Collaborative Food Recommendation via Multimedia Analytics

Dr. J. McAllister

• Biophysical EMG Analysis for Intelligent System Control
• FPGA-based Graph Signal Analysis
• Machine Learning in Intelligent Autonomous Devices
• Quantum Acceleration for High Performance Data Processing
• Quantum Error Correction using Field Programmable Gate Array
            (EPSRC Doctoral Training Partnership with Keysight Technologies)

Dr. Maarten van Walstijn

• Virtual-Acoustic Musical Instrument Design

Dr. Michalis Matthaiou

• Super-directive antennas for massive MIMO
• Low-latency communications in the 5G era

Dr. Nikolaos Athanasopoulos

• Hybrid systems modelling and control for Industry 4.0
• Safe Cobotics for Industry 4.0

Dr. Neil Buchanan

• Practical solutions for frequency diverse arrays
• Self-steered antennas for wireless power transfer
• Novel Injection Locked Transceivers for RFID and Healthcare

Dr. Okan Yurduseven

• Compressive Imaging using Computational Techniques at Millimetre-wave Frequencies
• Reconfigurable Holographic Metasurface Antennas for Dynamic Beam Synthesis and Electronic Beam Steering Applications

Dr. P L Kilpatrick

• Autonomic Management in Parallel/Distributed Systems

Prof. R Woods

• FPGA acceleration in the Cloud
• FPGA Inspired Acceleration for Genomics Applications
• Sensor and Data Analytics Systems for Structural Health Monitoring in Smart Infrastructure

Dr. Robert Best

• Operation of Low-Inertia Power Systems

Prof. Seán McLoone

• Evolving Intelligent Behaviour in Cooperating Robots (EvoBots)
• Flexible automation and cobotics
• Intelligent systems techniques for improving manufacturing competiveness

Dr. Sandra Scott-Hayward

• Defending ML-based Network Security Systems from adversarial attacks
• Edge-based solutions to IoT attacks
• Privacy-aware cybercrime tracking

Prof. Vincent Fusco

• Secure Wireless Frequency Diverse Array Methods
• Broadcast and Multicast transmission using Circular Array
• Slow Light Radar Absorber

Dr. Vien Ngo

• Meta Learning for Deep Reinforcement Learning
• Training a chatbot in the wild

Dr. Youngwook Ko

• Hyper-dimensional random access with DNN-aided physical layer feature fusion
• Learning-driven physical layer wireless technology for programmable universal connectivity

CSIT based PhD Research Projects

A number of studentship based in CSIT are available.

Click here for further details

Leverhulme Interdisciplinary Network on Cybersecurity and Society (LINCS)

The list of 2019 LINCS funded projects is now available

You can download a list of all the projects here

Queen’s University/China Scholarship Council PhD 2019 Scholarships

The list of 2019 Queen’s University/China Scholarship Council PhD Scholarships is now active

You can view the scholarships here