University Health Network (UHN) is looking for an experienced professional to fill the key role of Postdoctoral Fellow in our Ajmera Transplant Program.
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. Find out about our purpose, values and principles here.
We seek Postdoctoral Fellow for a project in involving application of cutting-edge ML tools to longitudinal clinical, laboratory and molecular data.
This represents an exciting opportunity to learn how to develop clinical tools using Deep ML algorithms on large patient datasets with longitudinal clinical, laboratory and molecular data. The candidate would be co-supervised by two Principal Investigators.
• PhD received within 5 (or MD received within 10 years) in computational biology, computer science, engineering, statistics, or physics
• Published/submitted papers in genomics or machine learning research required
• Expertise in Python, C/C++ and Unix programming environments required
• Hands-on experience in high performance computing, especially for parallelizing code in C/C++ (openMP) and/or python in a cluster environment (Sun Grid Engine or Torque)
• Demonstrated capacity to work effectively in a multidisciplinary collaborative environment
• Effective organizational, time management and prioritization skills
• Strong problem recognition and problem-solving skills
• Strong verbal and written communications skills
• Ability to effectively work as part of a team as well as independently
More information and apply here.