We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms.

We welcome application from individual with experience in: 

 

The post holder will be based in the Department of Biomedical Computing as part of the School of Biomedical Engineering & Imaging Sciences, King’s College London, a vibrant community of engineers designing and translating technology into the clinical. This role will be supported by the Quality Management Systems team at London Institute for Health Care Engineering who will collaborate closely with the group to ensure internal and regulatory requirements are met for the developed quality management system.

 

We are looking for someone with a passion for translating deep learning models into the clinical as part of a team.  This role is focused on developing computationally efficient deep learning models to perform neuroimaging segmentation tasks to help inform treatment decisions within a busy neurosurgical centre.

 

In this role the successful candidate will develop deep learning algorithms and validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed tomography (CT). In this role the successful candidate will write and seek to publish the developed state-of-the-art algorithms in high quality medical image computing journals and conferences. The successful candidate will work with a three-person team of software engineers to integrated algorithms into the Epilepsy Navigation (EpiNav™) software platform for stereotactic neurosurgery planning. The successful candidate will help to support the team to formally document algorithms within a quality management system.

 

EpiNav™ provides state-of-the-art computer-assisted support for the planning of stereotactic neurosurgery procedures. It has been in daily clinical use at the National Hospital for Neurology and Neurosurgery for over 7 years aiding neurologist and neurosurgeons in the surgical treatment of over 150 patients with medically refractory epilepsy and brain tumour biopsy. This software enables clinicians to use complex multi-modal imaging to inform surgical decisions. Based on the early success of EpiNav™ to help improve patient care we are refining and streamlining the software so that it is suitable for use outside of a research setting.  The team is multidisciplinary consisting of experts in medical image computing, medical regulation, neuroimaging and neurosurgery.

 

This is a full time post (35 Hours per week), and you will be offered a fixed term contract until 31/7/2028