Application Deadline:17th December
The human body is complex and multi-scale; it contains ~37 trillion cells which interact and assemble into functional structures, tissues and organs. Pathological change can occur at any scale in this system, often marked by both morphological and molecular changes. Linking molecular markers, from spatial transciptomics to multi-scale morphological imaging data, would revolutionise our understanding, detection, treatment and prediction of many major diseases that burden today’s society.
However, there is a gap in linking transciptome data to 3D multiscale imaging of human organs. This PhD will focus on the development of computational tools to link cutting edge transciptomics data to the latest development in multiscale human organ imaging - Hierarchical Phase-Contrast Tomography1 (HiP-CT).
Hierarchical Phase-Contrast Tomography is a multiscale Synchrotron X-ray imaging technique which enables whole human organs to be scanned hierarchically from the whole organ at 20-8μm/voxel down to 1μm/voxel in local regions anywhere within the intact organ. It relys on the the exceptional coherence and high energy provided by the European Synchrotron Research Facility’s Extremely Bright Source (ESRF-EBS) (https://mecheng.ucl.ac.uk/HiP-CT).
You will be part of the HiP-CT team with the role to co-develop, the computational methods to intergrate single cell transciptome and spatial transciptomics data; with HiP-CT imaging data of human kidneys. (Figure 1.)
You will work closely with our collaborators at the University of Cambridge, where spatial transciptomic data is being collected. Making use of their databse of the single cell transcriptional signatures of all kidney cells, you will analyse newely collected correlated spatial transcriptomic data and HiP-CT data to identify morphological corrlates of transciptonal signatures2.
For further details regarding this PhD studentship can be found here:
https://www.ucl.ac.uk/intelligent-imaging-healthcare/case-studies/2022/nov/intergration-single-cell-transciptomics-multiscale-heirarchical-tomography
|