4-year PhD studentship: Understanding kidney pathophysiology using novel kidney MRI acquisition and image analysis methods - (ENG 1613)

This is an exciting opportunity to undertake a PhD to develop novel Magnetic Resonance Imaging methods to study kidney structure and function and establish MRI biomarkers using ex-vivo and in-vivo imaging measures. Nephrons are the basic functional unit of the kidney, an organ with a central role in maintaining homeostasis in the body. Quantitative MRI is being used to determine the microstructure of the kidney non-invasively, and measurement of nephron number is now a near possibility. Low nephron number increases the risk of chronic kidney disease, hypertension, and cardiovascular disease.

This PhD project will span the following areas of research activity:

1)      Ex-vivo imaging to study MRI contrast and nephron imaging. This will include the use of contrast agents, the development of deep learning algorithms for nephron imaging, and the correlation of histology with imaging data acquired at ultra-high field and clinical field strength scanners.  3D printing methods will be used to generate realistic kidney reference objects.

2)      The development of novel methods for kidney MR image acquisitions and analyses using artificial intelligence (such as Deep Learning and super resolution methods) to resolve key components of nephrons, glomeruli and tubules in-vivo.

3)      The use of in-vivo and ex-vivo methods to establish reference values and protocols for clinical renal imaging, including harmonisation of data collected across MR scanner manufacturers.

Ideal candidate will have a background in Physics, Chemistry, or bioengineering. They will be based within the University of Nottingham across the Sir Peter Mansfield Imaging Centre - School of Physics and Astronomy, School of Chemistry, Centre for Additive Manufacturing, with a secondment to the Centre for Advanced Imaging at The University of Queensland, Australia.

What skills will be developed? By the end of this project, the student will have excellent MR physics skills in quantitative MRI, be able to use and have learnt to programme an MRI scanner, understand MRI sequence design. They will have gained computational skills in Python for image processing and deep learning. They will have developed an understanding of the properties and synthesis of contrast agents and use of 3D printing methods.

The position is part of a Doctoral Training Partnership (DTP), in collaboration with the University of Queensland, that will have four students in the cohort to support and collaborate to deliver key aspects of the project. Informal enquiries can be directed to susan.francis@nottingham.ac.uk or derek.irvine@notingham.ac.uk.

Eligibility 

Applicants should have at least a 2:1 degree, or equivalent, in a project-relevant discipline.

How to apply

Please send copies of your covering letter, CV and academic transcripts to cfam@nottingham.ac.uk referring to the project title. 

Closing date: applications will be evaluated on a rolling basis until a suitable candidate is appointed.

Keywords: MRI, Contrast Agents, molecular characterisation. Additive Manufacturing

Please apply here https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx

When applying for this studentship, please include the reference number (beginning ENG and supervisors name) within the personal statement section of the application. This will help in ensuring your application is sent directly to the academic advertising the studentship.

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