60 machine-learning "https:" "https:" "https:" "https:" "Instituto de Sistemas e Robótica Porto" Fellowship research jobs in Canada
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Fellowship in Reinforcement Learning and Autonomous Laboratory Systems Department Research | Tang | Michael Smith Laboratories
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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
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, integrating and interpreting them across modalities remains a fundamental challenge. The successful candidate will develop computational and machine-learning frameworks for multimodal neuroscience data
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Columbia (UBC) Vancouver campus invites applications for a full-time Postdoctoral Research Fellow with expertise in artificial intelligence (AI), machine learning (ML), and data science. The position will be
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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
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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
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campus in British Columbia, Canada. Please refer to reference number EU-58948 during correspondence about this position. Please visit the researcher profile of the supervisor for this position to learn
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laboratory settings. A combination of field, greenhouse, laboratory, and computer-based activities. Accountabilities: The postdoctoral researcher will play a central role in advancing the research and
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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