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, interventional effects, multiple mediation), and advanced longitudinal modelling (mixed-effects models, growth curve models, latent class trajectories) with machine learning and AI-based approaches. The Lab is
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Assistant Professor- Health Informatics and Translational Digital Health Systems and Policy Research
QUALIFICATIONS The University of Toronto requires that candidates must have a PhD at the time of appointment, in one of the following fields: Health Informatics, Biomedical Informatics, Information
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Information Computational complexity in adiabatic quantum computation AI to boost quantum technologies (e.g., machine learning for quantum error prevention/mitigation/correction) Quantum machine learning
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(macro). Advances in cutting-edge technologies such as Machine Learning, Natural Language Processing, and Generative Artificial Intelligence have paved the way to exciting opportunities to transform health
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monitoring. Familiarity with computational image analysis, scripting (Python, MATLAB), or machine learning–based image workflows. Experience with method development, imaging assay optimization, or pipeline
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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