Research Fellow

About us

University College London (UCL) UCL is a multi-disciplinary university with a population of over 17,000 staff and 50,000 students from 150 different countries. Degree programmes are provided a broad range of disciplines. For more information, please visit http://www.ucl.ac.uk/about. UCL Mechanical Engineering has been pioneering the development of engineering education, having taught the core discipline for over 165 years. In 1847, UCL was home to the UK’s first ever Professor of the Mechanical Principles of Engineering, Eaton Hodgkinson. It was also where Sir Alexander Blackie William Kennedy introduced organized laboratory practicals in university education training; a world-leading educational innovation at the time.

About the role

This is your opportunity to work in a team applying state-of-the art foundation models within active learning frameworks to create the Human Organ Atlas (HOA) with one of the world’s newest and most exciting bioimaging techniques(see human-organ-atlas.esrf.eu). You will apply foundation models such as MedSAM to ultra-high resolution CT scans of human organs obtained using Hierarchical Phase-Contrast Tomography (HiP-CT) (mecheng.ucl.ac.uk/HiP-CT) to segment tissue structures of interest. You will both implement and co-ordinate a large group of researchers performing image pre-processing, active-learning and application of foundation models. The foundation models will enable quantification and statistical analysis of morphological tissue structures, which will be applied to solve key biomedical challenges working with clinicians and biologists worldwide. Based at the Bloomsbury campus, you will also travel regularly to the European Synchrotron (Grenoble) helping to train others in image analysis and annotation. The post is funded for 2 years in the first instance, with the possibility of renewal.

About you

The successful applicant will have experience and enthusiasm for co-ordinating data preparation and quality evaluation as well as for application of ML models. They will understand the role and importance of human annotators in active learning frameworks and be excited to co-ordinate and participate in labelling and proof-reading efforts of the wider consortium. You will be interested in how the morphology of tissue structures can be quantified to understand physiological and pathology variation and be committed to making both data and research findings FAIR. The post-holder will need to show a high level of initiative working within an international multidisciplinary group dedicated to developing an open access Atlas of the Human Body. The post-holder will have experience of development in the imaging sciences to answer biomedical and clinical research questions, as well as a strong background in applying reproducible segmentation workflows for large im aging datasets.

What we offer

Depending on experience this will be a grade 7 or 8 role. For information about our rewards and benefits please visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits.

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 LGBTQI+ people.

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