190 machine-learning "https:" "https:" "https:" "https:" "The Open University" research jobs in Canada
Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- University of British Columbia
- McGill University
- Ryerson University
- Nature Careers
- Northern Alberta Institute of Technology
- Queen's University
- University of Toronto
- Dalhousie University
- SAIT Polytechnic
- University of Saskatchewan
- Fields Institute
- Institut national de la recherche scientifique (INRS)
- Mount Royal University
- OCAD University
- Perimeter Institute for Theoretical Physics
- The University of British Columbia (UBC)
- University of Waterloo
- 7 more »
- « less
-
Field
-
Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
-
Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Fellowship in Reinforcement Learning and Autonomous Laboratory Systems Department Research | Tang | Michael Smith Laboratories
-
Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
-
machine learning with single-cell genomics, spatial omics, and systems biology, supported by strong collaborations across UBC and internationally. Project Recent advances in single-cell and spatial omics
-
and learning environment for all our students, faculty, and staff. To learn about the Irving K. Barber Faculty of Science, go to https://science.ok.ubc.ca/ . For more information about UBC resources
-
, integrating and interpreting them across modalities remains a fundamental challenge. The successful candidate will develop computational and machine-learning frameworks for multimodal neuroscience data
-
Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 9 days ago
for beta-cell research. For those interested, there is also an option to learn and use in vivo diabetes models. Collaborative and Supportive Environment: You will collaborate closely with experienced
-
Computational complexity in adiabatic quantum computation AI to boost quantum technologies (e.g., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning Quantum cloud
-
Prepare and submit scientific manuscripts, posters and presentations for the ZIKV-IPD-MA-2S study accordingly Attend relevant workshops and conferences as necessary Learn new skills and contribute to other
-
Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a closely related technical field. Demonstrated knowledge of or interest in Indigenous Knowledge Systems and interest in applying IKS