Research Fellow in Medical Image Analysis & Machine Learning

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 UCL Hawkes Institute is a multi-disciplinary research grouping at the intersection of UCL’s engineering and health activities that focuses on advancing healthcare technology. The institute capitalises on UCL’s unique combination of research excellence in computational, engineering and medical sciences.

About the role

This post will develop and evaluate novel artificial intelligence algorithms that allow the use of MRI data that are saved in the standard way to provide accurate and precise quantification of the distribution of iron load in the brain.

Depending on the start date, this role is funded for 4 months.

About you

The successful candidate is expected to have a good PhD in Imaging Science, with significance experience in developing and evaluating advanced artificial intelligence algorithms for quantitative susceptibility MRI (QSM).

What we offer

As well as the exciting opportunities this role presents, we also offer great benefits. Please visit https://www.ucl.ac.uk/work-at-ucl/rewards-and-benefits to find out more.

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; and for our Grade 9 and 10 roles, women.

Our department holds an Athena SWAN Gold award, in recognition of our long-term commitment and 'beacon' status in advancing gender equality.

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