Advances in imaging technologies have transformed our ability to observe complex biological and physical systems. However, many widely used imaging techniques remain fundamentally limited in the level of spatial detail they can capture directly. Overcoming these limitations using computational approaches represents a rapidly growing area of research with the potential to unlock new insights across the life sciences, engineering, and data science.

We're seeking a motivated candidate to undertake a PhD to explore novel computational strategies to enhance the effective resolution of imaging data. The research will focus on developing and validating advanced mathematical and algorithmic approaches capable of extracting additional structural information from new and existing imaging datasets.

The successful candidate will work at the interface of computational imaging, applied mathematics, and biomedical measurement science, developing software tools and reconstruction techniques that can extend the capabilities of widely used imaging systems. The project will involve designing and implementing advanced computational methods for analysing imaging data, testing and validating approaches using experimental datasets, and exploring the potential for these approaches to be applied across the sciences and beyond.

This interdisciplinary project combines elements of optics, computational modelling, image analysis, and software development, providing an excellent opportunity to contribute to emerging approaches in computational imaging.