We will rapidly progress a synthetic vaccine against the novel Coronavirus into human studies within months. We have determined the genetic sequence (code) for the dominant surface exposed protein of the virus, the key target for protective immune responses. We have modified this sequence to express a highly stabilised version of the protein, maximising its potential to evoke protective antibodies. We have used this modified sequence to generate a ribonucleic acid (RNA) based vaccine that can be amplified within cells following injection, maximising its expression. Our RNA vaccine delivers the genetic instructions that tell muscles to make the viral surface protein which alerts the immune system to make protective antibodies. The advantage of our fully synthetic manufacturing process means that millions of doses can be made within weeks. This project will support clinical grade manufacturing of our candidate vaccine, preclinical safety testing and healthy volunteer studies to assess safety and immune potency of our vaccine. Should this first phase be successful we would progress to wider clinical testing, including studies to determine its protective effects against natural infection before making our vaccine widely available.

The AdS/CFT conjecture provides an exact description of string theory in negative spacetime curvature in terms of conformal field theory (CFTs) that lives on the boundary. These CFTs are usually strongly coupled though, which makes them difficult to study using standard perturbative methods like Feynman diagrams. We will use non-perturbative methods such as the conformal bootstrap and supersymmetric localization to study these CFTs at strong coupling, which will allow us to understand the dual string theory at strong coupling.

Aim of the PhD Project: Develop advanced ultrasound technology for high spatial and temporal resolution in vivo imaging of gut structure and function Develop optimised signal and image processing and machine learning technology in the presence of fat layers and tissue motion Study the impact of nutrient intake, inflammation and therapeutic agents on gut structure and microcirculation during mucosal healing in vivo Project Description: Recent advances in our understanding of the gut demonstrated that it is not only crucial for nutrient absorption but is also an integral part of the body's immune system. A healthy gut benefits nearly every aspect of human health, protecting us from nutrient deficiencies, inflammation, obesity, diabetes, immune diseases, infections, heart disease and cancer. There is now also overwhelming evidence that a healthy gut protects against many mental health disorders including depression, anxiety and autism. The ability to quantitatively assess gut health, identify pathological conditions (e.g. inflammation), and monitor the gut's ability to repair (mucosal healing) and respond to food intake and therapeutic agents, is key to further our understanding of this complex system, to the development of new drugs, and to the clinical management of patients with gut disorders and drug development. Recent clinical observational data and real-world evidence support the use of mucosal healing as a clinical endpoint in treatment of Inflammatory Bowel Disease (IBD). However the gut mucosa takes a long time to heal and therefore objective evidence of inflammation of the bowel and longitudinal changes to mucosal healing are necessary when making clinical decisions. However, currently our ability to measure gut health in vivo is very limited, and often involves either indirect or invasive procedures. Microvascular blood flow in the gut reflects changes in tissue activity. There is compelling evidence that specific regions of the gut precisely regulate their own blood flow to meet the local demands of absorptive, metabolic and repair processes. There is evidence that particular nutrients and metabolites, as well as some therapeutic agents, stimulate greater changes in blood flow which are correlated with reduced inflammation and improved mucosal healing. However, to date these changes in blood flow have mainly been studied invasively or in ex-vivo tissues. Several recent advances in biomedical ultrasound, including 1) ultrafast data acquisition with up to tens of thousands of imaging frames per second, 2) microbubble contrast agents allowing high contrast imaging of blood flow, and 3) super-resolution ultrasound achieving sub-diffraction limited resolution, have made it possible to non-invasively image in deep tissue the microvascular morphology and flow dynamics with a resolution of tens of microns. We have been among the first to demonstrate ultrasound super-resolution in vitro and in vivo. These advances in ultrasound present exciting opportunities for non-invasive in vivo measurement of gut structure and function, offering spatial and temporal resolution unmatched by other imaging modalities. However, significant challenges exist in imaging the gut using ultrasound, including the significant tissue motion, the presence of fat causing significant sound aberration and decreased image resolution. More recently we have been the first to demonstrate real-time super-resolution using of phase change nanodroplets. In this project we propose to develop advanced ultrasound imaging, image analysis, and machine learning technologies for robust measurement of gut microvascular structure and function, and apply the technologies in the setting of gut inflammation, mucosal healing and measurement of gut response to drug treatment.

Rifting of continents to produce new ocean basins is an important part of plate tectonics, and the geometry and magnitude of stretching has many implications for the development of hydrocarbon systems. Over the last decade numerical models have provided crucial insights into the rifting process, mainly using low-resolution 2D models. With advances in computational power it is now possible to numerically model rift evolution at a high-resolution in 3D to model how rift-scale fault arrays during rifting nucleate, propagate and grow through time. However, there are few observations of how normal fault arrays evolve at the rift scale to quantitatively test if the modern numerical models are producing fault array evolution predictions that are geologically realistic. This PhD will focus on quantifying the geometry and displacement history of fault arrays over complete rifts using large compilations of 3D seismic reflection and well data from data-rich and well-studied rifts such as the North Sea and NW Shelf of Australia. This will then be compared with the results produced by the 3D numerical model in order to test if it is geologically realistic. The key outcome of the PhD will be a better understanding of how fault arrays during early continental rifting (beta factors < 1.5) evolve at the rift scale. A newly validated numerical model of fault arrays in rift basins will be greatly applicable to other rift systems with sparsely populated data, covering a range of scales between regional large scale fault evolution systems, to mesoscale field outcrops and analogues, to the microscale using core and well image logs. This can provide better fault predictions on frontier regional seismic data, as well as establish sub-seismic fault density for fault seal analysis, ultimately reducing uncertainty in an extensional fault regime.