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Tom Vercauteren

Top university

1 year ago

Anatomy localisation in X-ray fluoroscopy videos for mechanical thrombectomy King’s College London in United Kingdom

Degree Level

PhD

Field of study

Neuroscience

Funding

Funding details are not explicitly stated in the post. Please refer to the official application page for information regarding stipend, tuition coverage, and other financial support.

Deadline

Expired

Country flag

Country

United Kingdom

University

King’s College London

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Keywords

Neuroscience
Computer Science
Biomedical Engineering
Artificial Intelligence
Health Science
Computer Vision
Stroke
Human Anatomy
Neuroradiology
Thrombectomy
Medical Robotic

About this position

This PhD opportunity at King's College London focuses on developing advanced computer vision and AI methods for anatomy localisation in X-ray fluoroscopy videos, specifically for mechanical thrombectomy procedures in acute ischemic stroke treatment. The project is highly interdisciplinary, involving collaboration between academic supervisors Professor Tom Vercauteren and Dr Thomas Booth, and industry partner Telos Health, represented by Konrad Leibrandt. The research aims to improve spatial understanding for interventional neuroradiologists by automating the identification of anatomical structures in real-time surgical imaging. Candidates will work closely with clinical experts to build annotated datasets and validate new algorithms.

The position is open for a February 2026 start, and applicants should have a strong background in computer science, biomedical engineering, or related fields, with skills in machine learning and medical imaging. Funding details are not specified; applicants should consult the official application page for more information.

To apply, visit the Surgery CDT website and follow the application instructions. This is an excellent opportunity for those interested in the intersection of medical robotics, AI, and clinical impact.

Funding details

Funding details are not explicitly stated in the post. Please refer to the official application page for information regarding stipend, tuition coverage, and other financial support.

What's required

Applicants should hold or expect to obtain a first or upper second class degree (or equivalent) in a relevant discipline such as computer science, biomedical engineering, medical physics, or a related field. Experience with machine learning, computer vision, or medical imaging is highly desirable. Strong programming skills and the ability to work collaboratively in interdisciplinary teams are preferred. English language proficiency is required as per King's College London standards.

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Professors

Professor at King's College London

University Name
Country flag

United Kingdom

Research Interests

Medical Imaging

Radiology

Optical Imaging

Neuroanatomy

Computational Imaging