Job Posting# 898474
TIER (The Institute for Education Research)
General Surgery (Surgical Artificial Intelligence Research Fellowship)
37.5 hours per week
Temporary Full-time (1 year; beginning August 2022)
University Health Network (UHN) is looking for an advanced trainee to fill the key role of Postdoctoral Fellow in the Surgical Artificial Intelligence Research Fellowship.
Transforming lives and communities through excellence in care, discovery and learning.
The University Health Network, where “above all else the needs of patients come first”, encompasses Toronto Rehabilitation Institute, Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre and the Michener Institute of Education at UHN. The breadth of research, the complexity of the cases treated, and the magnitude of its educational enterprise has made UHN a national and international resource for patient care, research and education. With a long tradition of groundbreaking firsts and a purpose of “Transforming lives and communities through excellence in care, discovery and learning”, the University Health Network (UHN), Canada’s largest research teaching hospital, brings together over 16,000 employees, more than 1,600 physicians, 8,000+ students, and many volunteers. UHN is a caring, creative place where amazing people are amazing the world.
University Health Network (UHN) is a research hospital affiliated with the University of Toronto and a member of the Toronto Academic Health Science Network. The scope of research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care. Research across UHN's seven research institutes spans the full spectrum of diseases and disciplines, including cancer, cardiovascular sciences, transplantation, neural and sensory sciences, musculoskeletal health, rehabilitation sciences, and community and population health. Find out about our purpose, values and principles here.
The Surgical Artificial Intelligence Research Academy is looking for a 1-year research fellow starting August 1st 2022. Candidates should have an MD degree and have either completed surgical residency or in the process of completing it. Any surgical subspecialty is acceptable.
Projects in our lab are dedicated towards research and innovation in areas related to intra-operative performance augmentation, robotic surgery and telecoaching. We use various methodologies, including artificial intelligence, AR/VR modelling, and simulation-based training to improve patient outcomes through surgical excellence. The Lab has partnerships with the Vector Institute, one of Canada’s largest hubs in artificial intelligence research (located at the MaRS Discovery District), and a multitude of academic institutions located throughout Canada, US, Europe, Japan and South America.
The successful applicant will be expected to work within a multidisciplinary team, including clinicians, engineers, computer scientists, artificial intelligence scientists and game developers. The aim of the lab is to develop and validate new technologies and methodologies to improve surgical performance. Examples include computer vision deep learning models that are capable of identifying surgical anatomy and augment surgeons’ mental model, telestration tools for live on-site and remote telecoaching, intra-operative navigation and post-operative video analysis, the use of haptic devices and machine learning for performance assessment, and video games for team-training.
With the appropriate supervision, the Research Fellow will be expected to lead and implement research studies including drafting research questions and methodologies, collect data, annotate surgical videos for machine learning, work with data scientists to develop and train AI models, apply for grants, write manuscripts for publication, and travel to national and international meetings for presentations. Other responsibilities include planning, implementing and coordinating all aspects of data collection and fully participating in project design, participant recruitment, data analysis and literature review. The Research Fellow will also be expected to attend weekly research meetings and make meaningful contributions to the advancement of the laboratory’s aims.
Given UHN and the Surgical AI Research Academy’s geographic location in downtown Toronto, there will be multiple opportunities for collaboration throughout the larger University of Toronto community and its entire network of clinicians and scientists. Opportunities to attend departmental seminars, conferences will be supported, and career-relevant initiatives (e.g. courses, conferences, travel to work abroad with a partner laboratory).
- PhD received within the past 5 years and/or MD received within the past 10 years; undergoing surgical training or have finished surgical training in any surgical subspecialty
- At minimum, 3 years of research experience, statistical analyses experience and manuscript preparation
- Experience in computer science, programming, machine learning/artificial intelligence, surgical education, and simulation-based training preferred
- Ability to write scientific communications and present work
- Statistical software and performing data analyses experience
- Excellent organizational and analytical skills, along with a high degree of independence and flexibility to thrive in a novel and rapidly evolving research environment
- Strong verbal and written communications skills
- Strong work ethic and excellent time management skills
- Ability to effectively work as part of a team as well as independently
Vaccines (COVID and others) are a requirement of the job unless you have an exemption on a medical ground pursuant to the Ontario Human Rights Code.
If you are interested in making your contribution at UHN, please apply on-line. You will be asked to copy and paste as well as attach your resume and covering letter. You will also be required to complete some initial screening questions.
For current UHN employees, only those who have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN's attendance management program, and possess all the required experience and qualifications should apply.
UHN thanks all applicants, however, only those selected for an interview will be contacted.
UHN is a respectful, caring, and inclusive workplace. We are committed to championing accessibility, diversity and equal opportunity and welcomes all applicants including but not limited to: all religions and ethnicities, LGBTQ2s+, BIPOC, persons with disabilities and all others who may contribute to the further diversification of ideas. Requests for accommodation can be made at any stage of the recruitment process providing the applicant has met the Bona-fide requirements for the open position. Applicants need to make their requirements known when contacted.