Applications are invited for theAstra-Zeneca Non-Clinical PhD Studentship - Multimodal and multiscale imaging: interrogating renal morphology and function across the disease landscape.The successful applicant will be working on collaborative project jointly supervised by the Professor Ferdia Gallagher (Department of Radiology) and Dr Richard Goodwin (Astra-Zeneca) and will have the opportunity to work across both sites.

Project Details:

As part of this studentship, we will jointly evaluate how metabolic measurements from imaging and tissue can be used to phenotype kidney disease. The goal is to create a multiscale and multimodal model to better stratify patients, to predict therapy response, improve detection of early response to treatment, and identify new metabolic targets for therapeutic innovation.

This project will bring together groups of researchers working in imaging data integration, bridging across a range of scientific and clinical disciplines. We will use renal disease, including diffuse renal disease and cancer, for proof-of-concept data and the project will facilitate new academic-industry partnerships. It will identify key aspects of metabolic imaging that could be used as diagnostic, prognostic and predictive biomarkers. A key aim will be to integrate these diverse datasets across scales. We will utilise artificial intelligence and machine learning approaches to evaluate the molecular drivers for the metabolic signatures of disease on imaging across disease settings. We will create a powerful and versatile model for probing renal metabolism across spatial scales. The impact of the models will be analysed and validated in datasets from multiple sites.

In summary, this studentship is an exciting opportunity for a talented researcher to investigate the potential role of novel clinical and tissue imaging methods to better understand renal disease. The project has the potential to help improve human health in the future as these techniques become more widely available in clinical practice.

Candidate:

We are looking for a highly motivated and enthusiastic individual capable of thinking and working independently. Applicants should have or shortly expect to obtain a first or high 2:1 bachelor's degree from a UK university, or an equivalent standard from an overseas university, in a relevant subject such as imaging, physics, biology, biochemistry, chemistry, computational science, data analysis, artificial intelligence, machine learning, or medicine.

Funding:

The funding for this post is available for 4 years. Funding will cover the student's stipend and tuition fees at the UK rate. This studentship is also open to overseas students who meet the UK residency requirements (home fees) or who can cover the extra costs associated with international student fees through scholarships or funding schemes. Students may not supplement fees via self funding.

The deadline for applications isSaturday 30th Nov 2024.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.