Genomic surveillance, i.e. using a pathogen's genetic blueprint to track it's spread in response to control measures, has become a key tool in contemporary disease management. This approach can now be deployed almost anywhere and conducted in near real-time to inform rapid and targeted interventions. Yet genomic surveillance is typically applied to emerging diseases with pandemic potential (e.g. SARS-COV-2) in high-income countries. I propose repurposing genomic surveillance for endemic zoonoses, diseases that spread from animals to people, such as rabies, that inflict a major preventable disease burden in many low- and middle-income countries. Such an approach would simultaneously improve surveillance for emerging infectious diseases through locally relevant capacity strengthening and provide the means to develop cutting-edge methodologies and capacities in "pandemic peacetime", whilst generating visible, tangible impacts on public health. My proposal focuses on developing and optimising an accessible toolkit for generating and interpreting rabies virus genetic sequence data, supporting the global strategy to achieve zero human rabies deaths from rabies spread by domestic dogs by 2030. Genomic surveillance can play a key role in resolving complex transmission dynamics, detecting introductions and identifying their sources. This epidemiological understanding is important for both designing and evaluating national rabies elimination programmes, as they are increasingly rolled out. The proposed work encapsulates novel laboratory techniques to generate sequences in resource poor settings, and contemporary methods for analyzing these data to track rabies spread and persistence, both locally within communities and longer-range movement across countries and regions. I will deploy this toolbox through my extensive international collaborations across Africa, Asia and Latin America to address specific questions to support rabies elimination programmes in practice, building local capacity and expertise for routine in-country genomic surveillance.

Traditional endoscopes comprise many thousands of optical fibres resulting in sizable systems. Here in Glasgow we are developing an endoscope the width of a single human hair. This new approach gives images of hard-to-reach areas, but sometimes sound is important too. The aim of this project is to extend the functionality of our endoscope to give both images and sound. We will achieve this through high-speed homodyne imaging of the back scattered light. This will involve skills in optical design, algorithm development and high-speed computing. Beyond the technical aspects of the project the student will interact strongly with our external collaborating organisations.

FUSION envisions immersive technologies that create hybrid experiences continuously in everyday life. Immersive technologies will fundamentally change how we experience reality and connect with each other. This change presents unresolved challenges for how we will behave, interact, and relate to each other in a possible future where XR is always available. There is a present-future gap in immersive technologies because we do not yet understand how to stabilise interaction in hybrid reality/virtuality. Because individuals can experience materially different realities, interaction can destabilise without shared points of reference. Collisions, gaps, and mismatches between social signals as individuals move across the XR continuum are also a source of instability. To realise the potential of XR to bring us together, we need new models and techniques for enabling stable interactions in XR. FUSION proposes a novel fusion of social signals between individuals and across realities to improve how we interact in XR. This approach will advance our understanding of how people experience hybrid reality/virtuality together, enable new measurements of stability during hybrid interactions, and improve the quality of interaction in XR. FUSION will produce novel models of social signals during hybrid interactions and establish the first measurements of stability and quality for interaction in hybrid reality/virtuality.

Natural tissue is a complex interplay of various components. A key parameter of the stability of natural tissue is the spatially controlled formation of layered structures. Recently, we could show the formation of hydrogels with significant mechanical properties via incorporation graphitic-Carbon Nitride (g-CN). The PhD student will study the formation of complex hydrogel architectures and their mechanical properties via incorporation of g-CN into synthetic hydrogel materials. Both synthetic and analytical tasks are part of the project to assess structure-property relationships. The final goal is to fabricate a composite hydrogel that mimics natural tissues regarding mechanical properties and water content.

To be added.