The University of British Columbia (UBC) is offering a fully funded Ph.D. position for a promising candidate to conduct research in the realm of machine learning applied to medical imaging, specifically focused on the diagnosis and management of venous thromboembolism (VTE). This role is pivotal in developing a novel AI-powered multi-anatomy ultrasound platform to enhance VTE management. The candidate will engage closely with a multidisciplinary team at the forefront of biomedical engineering research.

The research will focus on developing AI-powered techniques for the early and accurate diagnosis of venous thromboembolism, including deep vein thrombosis and pulmonary embolism, using advanced ultrasound technology.

Eligibility 

• A Master’s degree in Computer Science or similar fields Strong knowledge of mathematics and statistics
• Experience using deep learning for solving medical imaging challenges (classification, detection, segmentation)
•  Proficiency in programming languages: Python, Matlab, and C++
• Familiarity with deep learning frameworks: PyTorch, TensorFlow, or equivalents. Excellent communication and writing skills
• Proven publication records in top machine learning or medical imaging conferences