Skip to main content
What do you want to do?
Foundation
Undergraduate
Postgraduate
International
Advanced Clinical Practice
Aerospace Engineering
Anthropology
Arts and Health
Biomedical Sciences
Business School
Chemical Engineering
Civil Engineering
Clinical Education
Computer Science
Creative Writing
Criminology
Design School
Digital Media
Economics and Finance
Education
Electronic and Electrical Engineering
English
Environmental Sciences
Film Studies
Games Design
Geography
Global Challenges
History
Journalism
Law
Life Sciences
Mathematics
Mechanical and Automotive Engineering
Media and Communications
Medicine
Musculoskeletal Ultrasound
Music
Nursing
Occupational Therapy
Physician Associate
Physiotherapy
Politics and International Relations
Psychology
Public Health and Health Promotion
Social Work
Sociology
Sport, Health and Exercise Sciences
Theatre
Campus life
Study support
Student Services
Professional Development Centre
Research
Research degrees
Our partners and networks
International students
Study abroad and exchange
International Summer Schools
Global alumni
Business advice and support
Higher and Degree Apprenticeships
Employing our students
Research and development
Facilities and services
Procurement services
Help for SMEs
Business newsletter
Support Brunel
Contact us
News and Events
Brunel Alumni
Giving back to Brunel
Contact us
About
Colleges

Research degrees

PhD research student applications are welcomed by the IMS Research Group all year round.  Research students are valued members of our thriving, research-intensive team. We are particularly interested in supervising students' research in any of the broad range of topics listed above. Please note that the topic list is not exhaustive, so feel free to contact a member of IMS with your ideas. 

Some candidate PhD topics that group members are interested in supervising in the future may include, but are not limited to:

  • Delivering Student Centred Learning via Collaborative Digital Game-based applications.
  • Robot-Human Interaction
  • Virtual and mediated realities in Health care
  • Depth sensing technologies for automated falls prevention interventions and assistive equipment prescription.
  • 3D visualisation technologies to support clinicians and patients in carrying out falls prevention interventions
  • Physiological response based video summarisation
  • Multisensorial media-cues in e-learning.
  • Designing Web Content for Enhanced User Experience on an Internet-Connected Television Device
  • Olfactory-Enhanced Multimedia: A User’s Perspective
  • Self-beliefs in the Introductory Programming Lab and Game-based Fantasy Role Play
  • Improving patient education of falls risks via intelligent ‘human-like’ 3D gaming applications.
  • Sensor-based video summarisation
  • Delivering Student-Centred Learning education via intelligent gaming applications.
  • Exploring the value of intelligent robot-based assessments compared with traditional human-based assessment methods in higher education.

See below a list of available PhD projects in Computer Science that includes projects in our area:

Description
Supervisor
Funding
Ambient Vibration-Based Calibration of Finite Element Models of Bridges
Objective: The primary objective of this project is to develop a novel method for calibrating Finite Element models of bridges using ambient vibration data and drone imagery. This method will leverage...
Michael Rustell
Self Funded
Bridging the Gap: Integrating Neural Radiance Fields and Micro-drones for Enhanced 3D Volumetric Finite Element Analysis
Objective: The central objective of this project is the innovative deployment of Neural Radiance Fields (NeRFs) and micro-drones in the process of 3D volumetric Finite Element modelling of bridges. Th...
Michael Rustell
Self Funded
Few-Shot Medical Segmentation Using Deep Learning
We are seeking a highly motivated and talented candidate for a self-funded PhD position in the field of Few-Shot Medical Segmentation using Deep Learning. This opportunity is ideal for individuals wit...
Alina Miron
Self Funded
Explainable prediction modelling for early detection of risks in multiple long-term conditions using health records data
 Multiple Long-Term conditions (MLTC) are a major healthcare challenge associated with high service utilization and expenditure. In the project, the candidate will help develop robust and explainable ...
Self Funded
Development and Validation of Security Metrics and Predictive Models for Blockchain Ecosystems
Background: Blockchain technology is a transformative innovation that has the potential to disrupt various sectors including finance, healthcare, and governance. However, with its growing adoption, se...
Self Funded
Optimising end to end delay in 5G and Beyond networks
End to end delay is an important aspect in communication networks considering diverse applications ranging from healthcare to gaming. End to end delay is due to propagation, transmission, queuing and ...
Nila Nilavalan
Self Funded
Design and implementation of Explainable Trustworthy Artificial Intelligent System
Currently, the output of AI does not indicate the route or process the model has taken to obtain that output. So, the developers that developed the model will not be able to concisely conclude nor exp...
Tatiana Kalganova
Self Funded
Smart Homes: Intelligent Data Collection and Processing using Lynsyn
Electricity prices are constantly increasing, and household consumer demand response is a field gaining more interest. This allows the user to understand the behaviour of power consumption and therefo...
Tatiana Kalganova
Self Funded
Large Language Modeling (LMM) for unstructured dialogues
Language models such as ChatGPT have become increasingly popular in recent years due to their ability to generate human-like text and assist with a wide range of natural language processing tasks. The...
Tatiana Kalganova
Self Funded
Precision control of Nano-fuel production
Storing hydrogen nanobubbles in liquid carriers to produce hydrogen nano-fuels offers significant benefits in terms of efficiency, safety and sustainability. Hydrogen nano-fuels have great potential t...
Yang Yang
Self Funded
 

Fully-funded studentships

Brunel United Kingdom Europe International

Developing AI-based equitable risk prediction models for long-term conditions using longitudinal health data
Brunel United Kingdom Europe International

Investigating an AI-based framework for digital twins in manufacturing

Our funded studentships become available at different times of the year. Please keep checking our page regularly to see the latest funded opportunities. We also advertise all our funded studentships as soon as they become available on the @BrunelResearch twitter account.

View all studentships