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every colleague is valued and empowered to thrive. Our dedication to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join
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research and 35% teaching. Mellon Fellows will teach one course per semester. These courses will be small innovative seminars of their design or a section of Science, Technology, and Governance in
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, cluster randomised controlled trials implementation science, data linkage, data science, machine learning and artificial intelligence. In this role, you will have the opportunity to engage in a series of
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the
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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural
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You Completion (level A and B) or near completion (level A) of a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data. Demonstrated expert
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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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Details Title Postdoctoral Fellow in Machine Learning and Design of Biological Systems School Faculty of Arts and Sciences Department/Area Science Division Position Description A postdoctoral