Dr SB Bano
1 year ago
Fully–funded PhD Studentship in AI-Enabled Robot-Assisted Minimally Invasive Surgery University College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Fully Funded
Deadline
Expired
Country
United Kingdom
University
University College London

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Where to contact
Official Email
Keywords
Computer Science
Machine Learning
Biomedical Engineering
Medical Imaging
Artificial Intelligence
Computer Vision
Minimally Invasive Surgery
Big Data
Python
Pytorch
Tensorflow
Robotics Engineering
Surgical Sciences
About this position
BackgroundCurrent healthcare technologies face significant challenges especially for newly approved procedures due to their complexity, limited access to specialized surgical expertise, and the need for robot-assisted minimally invasive techniques to reduce risks to the patients. Robot-assisted minimally invasive surgery, especially in complex surgical procedures, offers many advantages, including reduced trauma, faster recovery times, and fewer complications. However, robot-assisted minimally invasive surgery presents substantial challenges for surgeons due to the limited visibility, constrained space, and high precision required during operations.To address these issues, there is an urgent need for intelligent robotic systems that enhance surgical precision and efficiency. AI-driven technologies, such as workflow recognition and surgical context understanding, can help in novice surgeon training and can also improve surgical outcomes and accelerate training for surgeons, especially in complex robot-assisted procedures.About the ProjectThis PhD project aims to develop advanced AI solutions to improve robot-assisted minimally invasive surgeries, with a focus on complex surgical procedures. The research will focus on designing AI models to automatically analyse surgical workflows, learn the key factors influencing surgery duration and surgical outcomes, build AI-enabled systems for robotic surgery to enhance surgical training and predict patient outcomes and model the impact of surgeon training on surgical outcomes.The project will leverage clinical data from real surgeries and high-fidelity training simulations to create AI models capable of predicting surgical outcomes and providing intraoperative decision support. The goal is to significantly improve both the learning curve for surgeons and the overall safety and effectiveness of minimally invasive surgeries.The project will be based at University College London (UCL) East Robotics facilities and at the UCL Hawkes Institute (formally known as the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS)), where students will have access to cutting-edge research facilities, well-equipped surgical robotics labs and expert mentorship.Person SpecificationRequired:· A first-class undergraduate degree and/or Master’s degree (or equivalent) in a relevant discipline such as AI, biomedical engineering, computer science, or robotics.· Strong skills in AI, machine learning, or computer vision.· Programming proficiency in Python and familiarity with AI frameworks (e.g., TensorFlow, PyTorch).· A keen interest in healthcare applications, particularly surgical technologies.Desirable:· Experience with medical imaging, surgical data analysis, or working in interdisciplinary research environments.· Interest in robot-assisted surgeries and their technological challenges.· Relevant publications in top-tier conferences/journals (MICCAI, IPCAI, ICRA, IROS)How to ApplyInterested candidates should first contact Dr. Sophia Bano at ([email protected]) with the following documents:· A one-page statement outlining your suitability for the project.· A two-page CV (including contact details for two referees).Formal applications must also be submitted via the UCL Computer Science MPhil/PhD website: https://www.ucl.ac.uk/prospective-students/graduate/research-degrees/computer-science-4-year-programme-mphil-phdInterviews will be arranged for shortlisted candidates by the supervisory team.
Funding details
Fully Funded
How to apply
? Contact Dr. Sophia Bano at [email protected] and submit formal applications via the UCL Computer Science MPhil/PhD website.
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