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on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected to develop deep learning models for analyzing whole-slide histopathology
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lead the in vivo functional analysis of this gene using conditional KO mouse models, with a focus on brain development, neuronal differentiation, and seizure susceptibility. All models are already
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deep learning techniques for analyzing high-dimensional omics data, identifying predictive biomarkers, and understanding cancer heterogeneity. Projects include modeling of bulk and single-cell
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environment allows for translation of novel methods to our cancer clinics in Canada (Vancouver, Victoria, and Kelowna) and beyond. Requirements: The ideal candidate will have a PhD in computational modeling
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, Victoria, and Kelowna) and beyond. Requirements: The ideal candidate will have a PhD in computational modeling/oncology, systems biology, applied mathematics, nuclear medicine physics, or a related field
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have a PhD in computational modeling/oncology, systems biology, applied mathematics, nuclear medicine physics, or a related field. Prior experience in at least one of the following is a requirement
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, and interpreting models, Analyzing genetics data (e.g. GWAS, eQTLs), including predicting variant effects, stratifying patients, identifying desired patients for recall, Designing, synthesizing, and
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Are you a Canadian PhD student with expertise on China interested in bridging academia and foreign policy? Department: Global Affairs Canada - Centre of China Policy Research and Coherence - OPR
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transportation operations and network modelling, accessibility analysis, data analysis (statistics and/or machine learning methods), and spatial mapping. Because the work will involve multiple years of daily
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understood, modeled, and ultimately reversed or rebuilt using bioengineering and synthetic biology approaches. The successful candidate will: Investigate mechanisms of T-cell development, aging, and thymic