PhD Scholarship in the Division of Biomedical Imaging: "Quantification of Novel MR Imaging Biomarkers using Machine Learning for Prognosis in Diabetic Kidney Disease"

University of Leeds - Faculty of Medicine and Health

Supervisors: Kanishka Sharma, Dr Steven Sourbron

Funding: Boehringer Ingelheim BEAt-DKD funding

A PhD scholarship in machine learning is available for UK and EU citizens only. The scholarship will attract an annual tax-free stipend of £14,553 for up to 3 years, subject to satisfactory progress, and will cover the UK/EU tuition fees.

You should hold a first degree equivalent to at least a UK upper second-class honours degree in a Computer Science, Mathematics, Physics, or a comparable subject area. This project would suit a student with strong mathematical background and excellent programming skills in languages such as Python, C++, Java, MATLAB, etc. Experience in areas such as deep learning and computer vision considered beneficial. It is not mandatory to have prior knowledge of multi-parametric MR imaging data but this can be advantageous.

The Faculty minimum requirements for candidates whose first language is not English are:

  • British Council IELTS - score of 6.5 overall, with no element less than 6.0;
  • TOEFL iBT - overall score of 92 with the listening and reading element no less than 21, writing element no less than 22, and the speaking element no less than 23.

Research Project:

You will participate in a major international EU-funded (public-private partnership) research project, Biomarker Enterprise to Attack Diabetic Kidney Disease (BEAt-DKD). The BEAt-DKD project aims to identify and validate improved prognostic biomarkers for development of effective and personalized treatments for Diabetic Kidney Disease (DKD).

This PhD position aims to support the BEAt-DKD project by developing efficient methods for quantification of (novel) imaging biomarkers in DKD from multi-centric, multi-parametric magnetic resonance imaging (MRI) data. The imaging work is led by the University of Leeds and involves close collaboration with other academic sites in the UK, France, Italy, and Finland.

You will develop new and innovative machine learning algorithms for automated segmentation of kidneys from MR imaging datasets. This will include quality assurance, automated segmentation of kidneys, and post-processing of multi-parametric MRI using state-of-art image processing algorithms ensuring high accuracy, precision, and reproducibility for translation at other international sites involved in the study.

Relevant links:

How to apply:

To apply for this scholarship applicants should complete a Faculty Scholarship Application form and send this alongside a full academic CV, degree transcripts (or marks so far if still studying), and degree certificates to the Faculty Graduate School ( Please indicate ‘BEAt-DKD Scholarship’ in the scholarship section of the form.

We also require 2 academic references to support your application. Please ask your referees to send these references on your behalf directly to by no later than Friday 29 September 2017.

If you have already applied for other scholarships using the Faculty Scholarship Application form you do not need to complete this form again. Instead you should email to inform us you would like to be considered for this scholarship project.

Any queries regarding the application process should be directed to 

For any project specific queries please email Kanishka Sharma ( directly.

Closing date for this Scholarship is Friday 29 September 2017.

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