Ph.D. Position in Machine Learning for Medical Imaging: The University of British Columbia (UBC) is offering a fully funded Ph.D. position focused on machine learning applications in medical imaging, specifically targeting venous thromboembolism (VTE) management through a novel AI-empowered multi-anatomy ultrasound platform.
Fully Funded Ph.D. Position in Machine Learning for Medical Imaging
Designation
Fully Funded Ph.D. Position in Machine Learning for Medical Imaging
Research Area
- Biomedical Engineering
- AI in Medical Imaging
- Deep Learning Techniques
Location
University of British Columbia, Vancouver, BC, Canada
Research conducted at the Center for Heart Lung Innovation, Providence Health Care’s St. Paul’s Hospital, Vancouver, BC, Canada.
Eligibility/Qualification
| Requirement | Details |
|---|---|
| Degree | Master’s degree in Computer Science or a related field |
| Knowledge | Strong understanding of mathematics and statistics |
| Experience | – Experience using deep learning for medical imaging problems |
| – Proficient in Python, Matlab, and C++ programming | |
| Working Knowledge | Familiar with frameworks such as PyTorch and TensorFlow |
| Skills | Excellent communication and writing skills |
| Publications | Evidence of contributions to top machine learning or medical imaging conferences |
Description
The prospective candidate will engage with clinicians, scientists, and engineers to advance VTE management by developing an AI-integrated ultrasound platform. This position will provide an opportunity to contribute significantly to the field of biomedical signal processing and image-guided surgery systems.
How to Apply
Interested applicants should send a cover letter and a CV combined into a single PDF document to Ilker Hacihaliloglu at ilker@mail.ubc.ca. When corresponding about this position, please mention the reference number GPS-58355.
Last Date for Application
Applications will be accepted until the position is filled.
This scholarship presents an excellent opportunity for candidates aiming to advance their careers in biomedical engineering and machine learning. Apply now to be part of this innovative research project!
