210 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" 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 Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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This research project, “Sensor-Free Machine Learning for Physiological Correction of Brain Functional Imaging: A Lifespan Pilot Study,” investigates how machine learning can be used to improve
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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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asset. General computer skills and ability to quickly learn computer programs (but not coding). Ability to work under deadlines with general guidance. Excellent organizational skills and demonstrated
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expertise in artificial intelligence (AI), machine learning (ML), and data science. The position will be a part of the Walk Tall research team based at BC Children’s Hospital. The Postdoctoral Fellow will
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research in cardiovascular and autonomic (i.e., bowel, bladder, sexual and cardiovascular) dysfunctions following SCI Demonstrated expertise in current machine learning techniques applied to biological
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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