PhD: Brain Imaging Phenotypes from Clinical MRI

The University of Edinburgh seeks a PhD student to build robust pipelines for extracting brain imaging phenotypes from more than 21,000 routine NHS Scotland MRI scans, tackling scanner and acquisition variability and generating age- and sex-specific reference data, on a funded four-year EASTBIO PhD with Dr Maria Valdes Hernandez and Professor Simon Cox.

About the Project

This 4-year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership (DTP). Detailed guidance on the application process, and the EASTBIO Application and Reference Forms can be found at How to Apply | Biology.

Please send your completed EASTBIO Application Form along with a copy of your academic transcripts (as a pdf) to INCR.PostgraduateRecruitment@ed.ac.uk. You should also contact your referees and ask them to submit their references (on the EASTBIO reference form template) to INCR.PostgraduateRecruitment@ed.ac.uk. by the application deadline of 16th November 2026.

In the rapidly evolving field of medical imaging, the integration and analysis of data from diverse acquisition systems present a critical challenge. Variability in imaging parameters and modalities hampers the consistency and reliability of analyses when combining data from different clinical settings and analysing longitudinal trajectories. Current harmonisation techniques are suboptimal in clinical settings. Phenotypes from images acquired with the most common protocol and under the scanners at major hospitals can bias automated pipelines, unfairly impacting patients imaged with disease-specific acquisition protocols and/or on scanners at health centres.

Another source of bias is caused by the population sample. Different levels of prevalence of diseases that reflect in structural brain changes also bias computational brain analyses. Automated phenotype extraction methods are often developed and validated in relatively homogeneous research datasets, whereas routine clinical imaging encompasses much greater variation in anatomy and pathology. The extent to which this heterogeneity affects measurement reliability, reference trajectories and comparability across datasets remains poorly characterised.

This project has the following aims:

1. Develop and validate robust extraction pipelines for technically challenging imaging phenotypes from heterogeneous routine clinical images: fractal cortical complexity, brain health index, white matter damage, brain volumes, white matter hyperintensities, and infarcts.
2. Quantify the influence of scanner, sequence, imaging modality, and acquisition parameters on each phenotype and develop harmonisation/QC strategies that preserve biological age- and sex-related variation.
3. Derive age- and sex-stratified clinical reference distributions for these phenotypes, with particular emphasis on measures for which large-scale reference values do not currently exist, and compare them with those acquired from research populations.
4. Test the reproducibility and clinical informativeness of these reference trajectories across independent datasets and diagnostic groups.

The student will access and analyse data inside the National Safe Heaven from the Scottish Medical Imaging Archive available through The Scottish Brain Health Data Pilot (21,197 MRI scans, 50% neuroradiologically ‘healthy’) acquired across NHS Scotland from 2010–2018, with 24 years of linked health records[1]. For aims 3) and 4) will access the in-house research datasets comprising the Mild Stroke Studies[2] the Lothian Birth Cohort 1936[3], and the Alzheimer’s Disease Neuroimaging Initiative database[4].

The student will receive training in medical image processing, big data analyses, working in the safe heaven, and advanced statistics. The principal supervisor will give day-to-day supervision in brain image processing and analysis methods, and the harmonisation of brain imaging data.

Funding Notes

This opportunity is open to UK and international students and provides funding covering stipend and UK level tuition fees. The University of Edinburgh covers the difference between home and international fees meaning that the EASTBIO DTP offers fully-funded studentships to all appointees. There is a cap on the number of international students the DTP recruits. It is therefore important for us to know from the outset which fees status category applicants will fall under when applying to our University.

Please refer to UKRI website and Annex B of the UKRI Training Grant Terms and Conditions for full eligibility criteria.

References

[1] DOI:10.1093/gigascience/giag072
[2] DOI:10.1177/2396987320929617
[3] https://lothian-birth-cohorts.ed.ac.uk/
[4] https://adni.loni.usc.edu/