Collaborative Postdoctoral Position - Medical Imaging AI

Sunday 12th May 2024

Contact Email for the Job Posting
Organization Department of Radiology, University of British Columbia
Location Vancouver, BC, Canada
Title Collaborative Postdoctoral Position - Medical Imaging AI
Closing date Dec 31, 2024
Description Job Title: Collaborative Postdoctoral Position - Medical Imaging AI
Organization: Department of Radiology, University of British Columbia
Collaborative Partner: Torus Biomedical Solutions
Location: Vancouver, BC, Canada
Application Deadline: June 15, 2024, or until the position is filled
Desired Start Date: 01 Sep 2024
Contract Type: 24 months / Full Time
Job Summary:
We have an outstanding opportunity for a Postdoctoral Research Associate at the Department of Radiology - University of British Columbia to engage in a closely collaborative research and development project with our industry partner, Torus Biomedical Solutions. The goal of this project is to develop a software solution that facilitates automatic image-based measurements within an existing intraoperative assessment product. The postdoctoral candidate will have the support, guidance, and supervision from the engineering team at the company led by Dr. Shahram Amiri as well as Dr. ilker Hacihaliloglu assistant professor at the Department of Radiology - University of British Columbia.
As a Postdoctoral Research Fellow, you'll play a pivotal role in leading and contributing to the development of a machine learning approach to automate intraoperative X-ray-based measurements in orthopedic surgery. Your tasks will include establishing a pipeline for generating synthetic fluoroscopic images, conducting a thorough review of cutting-edge techniques, and designing and testing deep learning neural networks for bone segmentation and landmark annotation. You'll also evaluate system performance in both simulated and real surgical environments. Working closely with a diverse team of engineers, researchers, and surgeons, your contributions can seamlessly integrate into an existing commercial product. Furthermore, your research findings will be submitted for publication in peer-reviewed journals.
Job Responsibilities:
• Conduct literature reviews and contribute to academic publications resulting from the project.
• Establish pipelines for generating synthetic fluoroscopic images/labeling from CT images.
• Design, develop, and optimize a convolutional neural network model tailored for automatic bone and implant segmentation, and annotation of key bone landmarks.
• Collaborate with interdisciplinary teams to ensure seamless integration of research outcomes into the final product.
• Participate in design and execution of performance testing and validation activities.
• Lead authorship efforts for organizing and publishing the research outcomes as white-papers, scientific abstracts and journal articles.
Job Qualifications:
• PhD in Computer Science, Biomedical Engineering, or a related field.
• Proficiency in Python-based machine learning, image processing and computer vision toolboxes (such as PyTorch, OpenCV, or scikit-image).
• Verifiable previous experience in applying machine learning to medical imaging, preferably with X-ray image modality.
• Track record of industrial product development experience or first author publications.
• Effective communication skills in English.
• For international applicants: willingness and ability to apply for a work visa and undergo the relocation process to Vancouver, BC, Canada.
How to Apply?:
Please email your application including a cover letter, your Curriculum Vitae, and names and contact info of three references to []. In your cover letter highlight your experience in machine learning & medical imaging, and describe your interest in the role, professional aspirations, and availability with respect to start date. Applications will be accepted until June 15, 2024, or until the position is filled.
Additional Information:
For more information or answer to specific question about this position, please email Dr. Shahram Amiri [].