All Projects
MRes Neurotechnology research projects available for the 2022-23 academic year are listed below, grouped by supervisor. Click a project title for a description of the project.
You can also see projects listed by research area on the main projects page.
If none of the projects listed is suitable for you, you may also contact your chosen supervisor directly to discuss alternative projects with them.
| Supervisor | Supervisor's Home Department | Project Title |
|---|---|---|
| Anil Bharath | Bioengineering | Neural Architectures for Predicting the Behaviour of Dynamical Systems |
| Shlomi Haar & Aldo Faisal | Brain Sciences & Bioengineering | Real-World Motor Learning in Embodied Virtual Reality |
| Adrien Rapeaux | Electrical & Electronic Engineering | Please contact to discuss projects |
| Christopher Rowlands | Bioengineering | A New Head Mounted Display Concept: Virtual Reality in a Pair of Sunglasses |
| Christopher Rowlands | Bioengineering | Analysing hyperspectral oncological images using cutting-edge data processing |
| Christopher Rowlands | Bioengineering | Building a next-generation scanning microscope |
| Christopher Rowlands | Bioengineering | Developing algorithms to sculpt light in 3D |
| Christopher Rowlands | Bioengineering | World's Fastest Video Camera |
| Simon Schultz | Bioengineering | Mapping amyloid plaques in whole brains using serial section two photon tomography |
| Barry Seemungal & Simon Schultz | Brain Sciences & Bioengineering | Assessing the effect of Dopamine on mutual information of Perceptuo-Motor Coupling in humans via transcranial magnetic stimulation |
| Barry Seemungal & Tim Constandinou | Brain Sciences & Electrical & Electronic Engineering | Use of electrophysiological and structural markers of inter-hemispheric connectivity to model the beneficial effect of noisy galvanic vestibular stimlation upon postural control |
| Reiko Tanaka | Bioengineering | Automatic quantification of fungal burdens in histology images using deep neural networks |
| Reiko Tanaka | Bioengineering | Development of computational tools to predict the occurrence of eczema using machine learning methods |