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Internship: MAMMOBOT: Robotic guidance and localisation during endoluminal procedures

Role title: Computer Vision and AI Researcher
Location of internship: Hamlyn Centre for Robotic Surgery, imperial College London (flexible with remote working)
Start date: ASAP
Duration: Up to 6 months
Salary: £1000 per month

Brief description of role:

This internship is funded by the project “MAMMOBOT – A flexible robot for early breast cancer diagnosis” which is supported by the CRUK-EPSRC Early Detection Innovation Award. This project aims to develop MAMMOBOT, a flexible steerable endoscopic robotic system that can safely navigate the mammary ducts, and harnesses novel sensors to highlight global duct abnormalities and imaging technologies to make local microscopic diagnoses. The internship will focus on robot localisation and guidance which are essential for thoroughly examining the ductal tree, targeting and retargeting pathological sites and deploying sensing probes in-vivo while keeping optimal tissue contact. Ductoscopic navigation through the mammary duct tree can be challenging due to the small field-of-view (FOV), coupled with the paucity of salient duct luminal features. Furthermore, tissue deformation and the complexity of the ductal tree anatomy make navigation disorientating, even for experienced operators.

The successful candidate will join the “Cognitive Vision in Robotic Surgery” research group at the Hamlyn Centre for Robotic Surgery, Department of Surgery and Cancer and will benefit from collaboration with the researchers of the group and its clinical collaborators. Training opportunities will also be provided at the Hamlyn Centre and Imperial College London.

Key objectives and responsibilities:

A robust robot localisation system will be developed using Computer Vision and Artificial Intelligence (AI) techniques. Depth reconstruction techniques will be used to recover geometric information from ductoscopic images. A robust robot localisation system will be developed based on the matching of ductoscopic data with a patient-specific ductal tree model. Deep learning approaches will be explored to map endoscopic video data to camera pose.

Candidate profile:

To apply for this position, you will need to have a strong background in at least one of the following areas:

  • Computer vision;
  • Machine learning;
  • Medical image computing and image guided intervention.

Application: To apply, please send a full CV to Dr. Stamatia Giannarou with Subject line starting with [Internship Mammobot]. 

 


Supported by the Hamlyn Endowment Fund and research grants from our funding bodies and industrial partners, we are always interested in providing positions for talented researchers in imaging, sensing and robotics. The Centre aims to attract the brightest students from around the world, drawn by the unique opportunities offered within the Centre’s multidisciplinary environment and state-of-the-art facilities.

In addition to the PhD Studentships advertised for specific research projects, we also support applicants for the following fellowships to work within the centre:

Please contact Marianne Knight if you want to discuss specific details about any of the fellowships listed above.