Venous thromboembolism (VTE), encompassing deep-vein thrombosis (DVT) and pulmonary embolism (PE), is a major global health concern with high morbidity and mortality rates. Early and accurate diagnosis is critical for timely intervention and improved patient outcomes. This research proposal aims to develop a novel, artificial intelligence (AI)-empowered, multi-anatomy ultrasound platform for enhanced VTE management.
The candidate will be closely interacting with clinicians, scientists, and engineers and will be part of the https://ultrai.med.ubc.ca/ lab. The successful candidate will be based at the University of British Columbia located in Vancouver, BC, Canada. The research will be conducted at the Center for Heart Lung and Innovation housed within Providence Health Care's St. Paul's Hospital in the heart of downtown Vancouver, British Columbia, Canada. The candidate will be a graduate student at the School of Biomedical Engineering.
Requirements:
- A Masters degree in Computer Science or similar.
- Good knowledge of mathematics and statistics.
- Experience in using deep learning techniques for solving medical imaging problems (e.g., classification, detection, segmentation).
- Experience in Python, Matlab, and C++ programming.
- Working knowledge with PyTorch, TensorFlow (or any alternatives).
- Excellent communication and writing skills.
- Publication records at top machine learning or medical imaging conferences.
Please email your cover letter, and CV combined into a single PDF document to ilker@mail.ubc.ca