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. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. Located in
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, or comparable research experience, along with significant experience in machine learning, computer programming, computational biological applications. A strong background in statistics and biology. Experience
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. This project will involve applying and evaluating statistical and machine learning models for data integration and interpretation. A strong foundation in statistical modeling will be essential for applications
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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, detection, and related imaging tasks Design self-supervised or weakly supervised learning approaches for large-scale datasets • Position 2: Postdoctoral Researcher in EHR-based Prediction and Clinical Risk
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
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of immune cell function. These projects are focused on making safer and more effective cell therapies (e.g., CAR-T) and gene therapies for cancer and beyond. We are an interdisciplinary lab spanning
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(thedonnellycentre.utoronto.ca ). Required Qualifications: We are looking for postdocs that have excellent molecular biology skills and/or a strong computational background including machine learning approaches. Candidates should