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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
Intelligent, Interpretable and Adaptive Design of Steel Structures using Deep Learning and NLP
The overall aim of this research is to develop a smart design assistant which is able to intuitively perform the design of complex steel structures to Eurocode Standards. Design errors are common, cos...
Self Funded
Disruptive Digital Experiences
Digital experiences deliberately go beyond simply communicating information - they seek to strongly engage, involve, and emotionally affect the user using digital means. A huge array of interactions a...
Self Funded
Brain wave analysis and modelling with graph signal processing
Brain wave analysis and modelling is an increasingly important research area, not least because of its applications in bio-medicine, rehabilitation, and next-generation human-computer interfaces. This...
Self Funded
Digital Stone: Robotic Construction of a Masonry Arch Bridge
Stone bridges and buildings were widely built up until the 1920s. They last for hundreds - and in many cases thousands of years, for example those built by the Romans. With 80% lower carbon emission c...
Self Funded
Using deep learning for weed detection
Although the deep learning area has made a major breakthrough in the latest developments, there are still numerous challenges that have to be resolved when working with real-world data. In this partic...
Self Funded
User experience in Extended Reality environments and applications
Extended Reality (XR), which covers Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR), is already in the rise with applications from manufacturing to health to gaming, to name but ju...
Self Funded
Exploring the potential of serious games to enhance user engagement with real-world applications
Serious games, which are defined as digital games that do not have entertainment as their main focus, have been shown to be an effective platform for improving training, education or modifying objecti...
Self Funded
Development of personalised services and applications for healthcare
The Internet of Things (IoT) is becoming a reality and is increasingly getting more integrated in our everyday lives. Its interplay with Mobile Computing is a key ingredient in this. Smartphones are e...
Self Funded
Building Information Model Development Using Generative Adversarial Networks
Generative Adversarial Networks (GAN’s), are an approach to generative modelling using deep learning methods, such as convolutional neural networks. Generative modelling is an unsupervised learning ta...
Self Funded
Energy and CO2 Awareness during Software Design and Development
An ever-critical topic is the emergence of Green Software Engineering and how software engineering influences the environment. This project aims to advance the state of the art by defining an approach...
Self Funded
 

Fully-funded studentships

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.

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