Intergration of single cell transciptomics & multiscale heirarchical tomography of whole human organ

PhD Studentship 23004 - Integration of single cell transcriptomics and multiscale hierarchical tomography of whole human organs - Ongoing Deadline

University College London working with ESRF, and part of the Centre for Doctoral Training in Intelligent, Integrated Imaging In Healthcare (i4health)

Supervision Team:
UCL: Prof. Peter D. Lee and Dr Claire Walsh
ESRF: Dr Paul Tafforeau
University of Cambridge: Prof Menna Clatworthy

Project Background

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.

The PhD project is jointly supervised by Prof. Peter Lee (Mech. Eng.) and Dr Claire Walsh (BioMed.Phy), with Prof. Menna Clatworthy (University of Cambridge and Wellcome Sanger Institute) and Dr Paul Tafforeau (ESRF, Grenoble France) where you will spend spend a portion of your time. The results will form part of the Human-Organ-Atlas.esrf.eu, a public database we’re compiling of our organs in health and disease, funded by the Chan Zuckerberg Initiative with a goal of eradicating disease.

Person Specification

Applicants should ideally have a first class undergraduate degree (or equivalent) in Physical Sciences (Computer Science, Engineering, Mathematics or Physics). Knowledge of image processing and strong computer programming skills are required. Applicants should have an interest in bio-medical imaging, and trasnciptomics. Excellent organisational, interpersonal and communication skills, along with a stated interest in interdisciplinary research, are essential.

Eligibility

The position is open to students on Home Fees and applicants whose first language is not English are usually required to provide evidence of proficiency in English by UCL. Please do not enquire about this studentship if you are ineligible. Please refer to the following website for eligibility criteria: https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/medical-imaging-mres-mphil-phd

How to apply:

Please complete the following steps to apply.

•    Send an expression of interest and current CV to: Prof peter.lee@ucl.ac.uk, Dr Claire Walsh c.walsh.11@ucl.ac.uk and cdtadmin@ucl.ac.uk
Please quote Project Code: 23004 in the email subject line.
•    Make a formal application to via the UCL application portal. Please select the programme code MRes Medical Imaging TMRMEISING01 and enter Project Code Integration of single cell transcriptomics and multiscale hierarchical tomography of whole human organs  - 23004 under ‘Name of Award 1’ 

Application Deadline: Ongoing until position filled