Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of British Columbia
- University of Toronto
- McGill University
- Nature Careers
- University of Victoria
- Canadian Association for Neuroscience
- University of Waterloo
- OCAD University
- Mount Royal University
- University of Saskatchewan
- Carleton University
- Dalhousie University
- Institut national de la recherche scientifique (INRS)
- National Research Council Canada
- Ryerson University
- University of Northern British Columbia
- University of Ottawa
- 7 more »
- « less
-
Field
-
approaches (based on functional programming abstractions) to optimize the implementation of machine learning models and other digital signal processing algorithms on a specific FPGA architecture to fit within
-
Sessional Lecturer - HIS311H1F Canada in the World Course Description: Ranging from the fifteenth through to the turn of the twenty-first century, students will learn about the treaties, trade
-
collaboration with industry partners. This work will apply optimal control theory, including machine-learning algorithms and Bayesian estimation, to coherent control of nitrogen-vacancy centers in diamond
-
Sessional Lecturer, INF2205H - Designing Sustainable & Resilient Machine Learning Systems with MLOps
University of Toronto Faculty of Information Sessional Lecturer Winter Term 2026 (January - April) INF2205H – Designing Sustainable and Resilient Machine Learning Systems with MLOps Course
-
environment. Proficiency in learning management systems and other computer applications as required.
-
University of Toronto Faculty of Information Sessional Lecturer Winter Term 2026 (January - April) INF2179H – Machine Learning with Applications in Python Course Description: Machine learning has
-
Learning Course Description: Machine Learning applications are increasingly utilized to make crucial decisions in many sectors of our economy and society. These include, but are not limited to, healthcare
-
development and target discovery challenges. Qualifications: PhD in bioengineering, computational biology, machine learning, systems immunology, or related discipline, obtained within the last 5 years, by
-
discovery challenges. Qualifications: PhD in bioengineering, computational biology, machine learning, systems immunology, or related discipline, obtained within the last 5 years, by the time of
-
this will include: Demonstrated expertise in data analysis and simulation Familiarity with C++; and proficiency in the use of ROOT and Geant4, and interest in machine learning techniques Knowledge