NOW CLOSED -Intergration of single cell transciptomics & Multiscale Heirarchical tomography of human

Full home student tuition fees and stipend of ca. £17,609 per annum (for up to 3 years, with possible 4th year if required.)

Intergration of single cell transciptomics & Multiscale Heirarchical tomography of human organs

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: 

Biological organisms are hierarchically structured, spanning from the RNA, or mRNA molecules of the transciptome to whole organs via cells and organotypic units. For humans, these scales span from the nanometre to the metre. There have been significant advances in imaging at both extremes, with developments in electron microscopy imaging RNA at the nano-scale, to clinical CT and MRI (100’s of microns) at the whole body scale. However, there is a gap in imaging techniques which span the scale from the micron to 100’s of microns, and thus link transciptome data to organ system level imaging data. Therefore, there is a drive to develop imaging techniques which achieve near micron resolution deep in soft-tissue. You will be part of a team developing a new technique that decouples resolution from specimen size using the exceptional coherence and high energy provided by the European Synchrotron Research Facility’s Extremely Bright Source (ESRF-EBS) upgrade to a 4th generation source. This technique, Hierarchical Phase-Contrast Tomography1 (HiP-CT), can achieve local cellular resolution of soft-tissues using phase propagated information. Specifically, 1 um voxels were achieved locally in a range of intact 150 mm diameter human organs, as shown for a human Kidney in Fig. 1) https://mecheng.ucl.ac.uk/HiP-CT). Your role will be co-developing, and applying strategies to intergrate single cell transciptome and spatial transciptomics data with HiP-CT imaging data. You will also examine other techniques such as histology and fluorescencne micsocopy as a means to integrate datasets. With our  collaborators at the University of  Cambridge, you will integrate single cell transcriptional signatures of all kidney cells, including those of relevance to inflammation and scar tissue formation, with the spatial transcriptomic images and morpholometric data of kidney structures2. 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.

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/mechanical-engineering-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: 22006 in the email subject line.
•    Make a formal application to via the UCL application portal https://www.ucl.ac.uk/prospective-students/graduate/apply . Please select the programme code MPhil Medical Imaging RRDMEISING01 and enter Project Code 22006 under ‘Name of Award 1’ 

Application Deadline:

Applications considered on a rolling basis until position is filled. Latest start date available Sept 2022.
If shortlisted, you will be invited for an interview.