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The fellow will be responsible for: Building collaborations with our multidisciplinary team (medical physicists, engineers, computer scientists, nuclear medicine physicians) to develop and implement innovative
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scientists, nuclear medicine physicians) to develop and implement innovative AI algorithms applied to medical images To lead effort on enabling translational and physician-in-the-loop AI solutions for medical
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. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health, bio-signal processing, and wearable
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PyTorch, TensorFlow, and Scikit-learn. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health
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midlife brain function and cognition. The applicant should be interested in applying multivariate and machine learning neuroimaging methods to the study of how chronological ageing, biological sex, and
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Department: Electrical, Computer and Biomedical Engineering Position supervisor: Dr. April Khademi Contract length: 1 year (with possibility of extension) Hours of work per week: 36.5 About Toronto
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processing, artificial intelligence, cognition and deep learning, machine learning, navigation and mapping, autonomous driving, assistive robotics, drones, dynamics and vibration, acoustics, medical imaging
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. The projects may also include to tackle benchmarking problems such as SAT, image processing, graph theories, boson/fermion sampling by applying classical machine/deep learning, neural network techniques and