MRC Investigator Scientist in Cardiac image analysis
Computational Cardiac Imaging Group
(3 Years fixed term)
Salary: £41,843 – £43,962 plus London allowances (£3,913 & £1,472) per annum
London, UK
The LMS is a world-class research laboratory where scientists and clinicians collaborate to advance the understanding of biology and its application to medicine. Funded by the MRC as part of UK Research and Innovation, the LMS has a collaborative working culture and new state-of-the-art building based in the heart of West London in the Hammersmith Hospital Campus. For more information, visit oreganlab.org.
The Computational Cardiac Imaging Group works at the intersection of clinical imaging, bioinformatics, computer vision and molecular cardiology to explore the mechanisms underlying heart function. The group uses machine learning to analyse cardiac motion for predicting patient outcomes, discovering potential therapeutic targets and identifying genetic risk factors. We use a flexible and inter-disciplinary approach to research that moves between individuals, populations and model organisms.
Applicants should have substantial research experience in biomedical image analysis including cardiac MRI. We are looking for expertise in computer vision approaches for cardiac image segmentation, motion analysis and registration. Experience of working with state-of-the-art deep learning algorithms is required. Knowledge of how to reconstruct 3D models from sparse image data would be an advantage. Familiarity with UK Biobank data or similar large-scale resources would also be helpful. This will also be an opportunity to innovate and develop new approaches for building rich image derived cardiac phenotypes and linking these with aging processes. Excellent programming skills in Python / C++ are needed, as well as experience of DL libraries and segmentation pipelines. Previous use of HPC environments would be an advantage.
The post offers an exciting opportunity to work at the cutting-edge of translational medicine research in a vibrant and supportive multi-disciplinary team that crosses traditional scientific domains. The post holder will have the opportunity to liaise with an extensive network of collaborators, attend scientific conferences, and publish the results of their work in leading journals. There is also a vibrant and supportive community at the LMS with outstanding opportunities for career development and training.