Snr Research Fellow Medical Image Computing CT Image Analysis

About us

UCL’s Department of Computer Science (CS) is a top-ranked Computer Science Department in the UK. In the 2021 Research Excellence Framework (REF) evaluation, UCL Computer Science was ranked second in the UK for research power and first in England.

The Centre for Medical Image Computing (CMIC) at UCL employs over 150 staff and students focused on the analysis of medical imaging modalities in a variety of organs and diseases. CMIC is located in Holborn in central London close to the British Museum and is a dynamic centre for medical research using cutting edge machine learning and clinical technologies.

About the role

The project is to quantify imaging features lung disease using computed tomography (CT), microCT and hierarchical phase contrast tomography at the Centre for Medical Image Computing at UCL.

The duties and responsibilities will include careful image analysis of high dimensional data and labelling to allow automatic or semi-automatic analysis of imaging features including disease progression modelling and fluid dynamics. The candidate will be expected to undertake research and development according to the work-plan of this collaborative project, and in particular to apply scientific rigour to this activity.

The role is funded until 31st March 2026 in the first instance

About you

The candidate needs to be motivated and able to work in a non-clinical environment with computer scientists and engineers. They will work at the boundary of existing and new knowledge with which to better characterise chronic lung diseases. The candidate should have research experience and domain knowledge of both clinical lung imaging and histopathology evaluation of the lungs.

The post holder will develop advanced algorithms, including convolutional neural networks, for the extraction of CT lung structures on a lobar basis across various spatial resolutions, as well as registration techniques for aligning longitudinal CT images to track disease progression. They will employ unsupervised learning to identify disease phenotypes linked to patient biomarkers and use computational fluid dynamics to gather functional insights from imaging data. Method validation and dissemination of research findings via high-impact publications and conferences are key responsibilities. Th e role involves collaboration with clinical and academic partners, contributing to the project work-plan, supervising students, and promoting research outcomes publicly. Compliance with UCL policies, fire, health, and safety regulations, along with ongoing professional development, is essential, and additional duties may be assigned as needed to meet project objectives.

A job description and person specification can be accessed at the bottom of this page. To apply for the vacancy please click on the ‘Apply Now’ button below.

If you have any queries regarding the vacancy or the application process, please contact Dr Joseph Jacob

What we offer

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Our commitment to Equality, Diversity and Inclusion

As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce. These include people from Black, Asian and ethnic minority backgrounds; disabled people; LGBTQI+ people Our department holds an Athena SWAN Gold award, in recognition of our commitment and demonstrable impact in advancing gender equality.

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