24 doctoral studentships are offered in cutting edge research areas including topics related with AI, Machine Learning, Renewable Energy, Human Wearable Devices, Modelling of Tumour growth and many others.
You will have the opportunity to be guided by world leading scientists in an exciting international environment in the heart of the City of London.
Moreover, you will be able to fully exploit the power of our new High Performance Computer (Hyperion) and world class laboratories and facilities. Our Doctoral College will support you with further training in diverse transferrable skills and networking opportunities enabling you to complete your doctoral training with an all-round preparation.
Value and eligibility
Please see the individual studentship pages below for further information on the value of the studentships as well as their respective eligibility requirements.
Available studentships
The following studentships are currently available across the School's research areas.
Studentships in Electrical and Electronic Engineering
Intelligent Wound Dressing for Accelerated and Controlled Healing of Burn Injuries (i-Heal)
This studentship aims to address the important clinical issue that burn wounds can be the most traumatic and physically debilitating injuries, leading to chronic irreversible scarring and increased mortality.
Innovative Sensor-Cloud for Sewer Monitoring and Management
This studentship aims to address one of the key technical challenges surrounding the ‘storm overflow of raw sewers into UK waters’ faced by the UK water companies.
Modelling the economic and environmental cost of raw materials for the global energy transition to 2050 using integrated life-cycle assessment of renewable energy systems and energy network modelling
This studentship will offer the student a chance to work with experts in the areas of system engineering, life-cycle analysis, environmental modelling, big data processing, renewable energy, and electrical networks.
Network Intelligence for Multipath Support in 5G/6G Networks
You will have the opportunity to work on efficient application of artificial intelligence and machine learning in support of traffic steering, switching and splitting for multipath delivery of Internet services in 5G/6G networks.
Countering Adversarial Attacks in Deep Reinforcement Learning Agents
This project aims to develop novel solutions to the potential attacks on DRL agent and will focus on the less explored impact on DRL agents.
Studentships in Civil Engineering
Artificial neural network based prediction formula for the behaviour of perforated steel shear walls reinforced with fibre-reinforced polymer sheets
This studentship will afford the student a chance to go deep in the areas of seismic design of steel structures, optimisation, advanced modelling, and machine learning.
Hydrodynamics of Novel Scour Protection Countermeasures for Monopile Offshore Wind Turbine Foundation
This studentship will afford the student a chance to go deep in the areas of fluid-soil-structure interaction, scouring and costal protection.
The influence of pile stiffness on pile capacity at working load
The research project investigates alternative low stiffness pile loads. The potential benefits could be the reduction in carbon heavy materials and the ability to repurpose existing sites during redevelopment.
Studentships in Mechanical Engineering and Aeronautics
Two-phase Cooling Systems for Electric Vehicle Battery Packs
This studentship afford the student a chance to go deep in the areas of multiphase flows and heat-transfer enhancement, as well as in technologies relevant to vehicle electrification.
SAFER: StAll FluttER on conventional and innovative wing structures
This studentship will afford the successful student a chance to gain deep understanding of unsteady aerodynamics and aeroelastic instabilities, as they work under with the academic supervisors and the industrial partner.
Failure modelling and lifetime prediction of structural battery fiber composites for next-generation electric aircraft
This studentship aims to develop a computational framework capable of simulating damage and failure in such multifunctional energy-storing composite materials/structures.
Multi-domain modelling of microsatellite propulsion systems with green propellants
This studentship will afford the student a chance to go deep in the areas of space propulsion, spacecraft design, energy storage and power management with an option of optimisation or control.
Experimental characterisation of high-speed two-phase expansion for power generation
This studentship allows the student a chance to explore fundamental features of high-speed two-phase flows of non-ideal fluids. These skills are expected to be sought after highly by industry.
Studentships in Mathematics
Symmetry Resolved Entanglement in Quantum Field Theory
This studentship will involve work on Entanglement Measures, with a focus on a recently proposed measured known as Symmetry Resolved Entanglement Entropy.
Phonon Effects on Transport in Weyl and Dirac Semimetals
This studentship will allow the student to acquire a strong expertise on topics at the forefront of research in an exciting and rapidly expanding field of theoretical condensed matter physics.
Higher-derivative systems with benign ghosts from integrable systems
This studentship involves working on integrable classical and quantum field theories.
Mathematical theory of tumour evolutionary modes
This studentship aims to develop a general mathematical understanding of how the diverse evolutionary modes observed in human tumours arise from their evolutionary parameter values and spatial structures.
Studentships in Computer Science
Geometric and topological methods for segmentation and analysis of three-dimensional cells observed with Electron Microscopy
This studentship allows the student to dive deeper into the areas of medical image processing and computational topology and geometry.
Next Generation Blockchains with Sharding
This studentship lies at the interface of distributed systems and cyber security, with the aim to develop the next generation of blockchains through a method known as sharding.
Improving Predictive Models with Causal Structure Learning
This studentship offers a chance to go deep in the areas comprising machine learning, statistical learning, and the acquisition of managerial skills to develop, manage, and communicate the research findings.
Data Visualisation mediated through natural language interaction
This studentship is at the forefront of research in Machine Learning, Visual Analytics and Information Visualisation.
Conservative Bayesian Assessment of Classifiers used for Malicious Network Activity Detection
The studentship will involve gaining an understanding of ML-based cyber-defence tools and developing novel Bayesian inference algorithms for the assessment of ML-based cyber-defence tools.
Weakly Relational Domains and Abstract Interpretation for Cyber
The studentship will investigate integrating work on lightweight and powerful Weakly Relational Domains into a non-relational abstract interpretation framework, and use the resulting system to analyse benchmark programs.
An Investigation of Student Learning in Computing Education Research
This studentship allows the student to dive deeper into the areas of student learning in computer science.
How to apply
When submitting your proposal application, enter the title of the research project and you will automatically be considered for the doctoral studentship.
You do not need to submit a proposal as part of your application as the project has already been outlined.
Closing date for 2022/23 applications: Please check the individual studentship pages for each relevant closing date.
Further information about when the outcome of the selection process will be announced, as well as when the candidate will formally start his/her doctorate, can be found on individual studentship pages.
Applications are welcome from individuals wishing to pursue research in any of the departments listed below. You are strongly encouraged to discuss your application in advance with a potential supervisor in the School. Please visit the departments pages to gather detailed information on each individual scholarship and apply online.
- Electrical and Electronic Engineering
- Civil Engineering
- Mechanical Engineering and Aeronautics
- Computer Science
- Mathematics.
When applying, please make sure that you have prepared the following supporting documents:
- Copies of Degree Certificates and Transcripts in official English translation – original will be requested before an offer is made
- Official work/academic e-mail addresses (not private ones) for two referees (one of which must be an academic)
- Proof of English Language proficiency (minimum average score of 6.5 IELTS, with a minimum of 6.0 in each of the four components) if English is not your first language. Not required if your Master’s degree has been awarded in an English-speaking country.
- Passport.
Email pgr.sst.enquire@city.ac.uk for further information about applying for the scholarships.