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, policy, energy conversion, new business models, techno-economic and life cycle analyses, machine learning, optimization, AI, intelligent networks, among others. The PDF will join a project in collaboration
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: Machine learning/deep learning model development for biomolecular data analyses and prediction Research Area: Data science and computational chemistry Required Skills: A Ph.D. in relevant field within
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of the following projects: The molecular regulation of insulin secretion. In particular, the characterization of new (unpublished) transgenic models to study SENP1 (e.g. PMID: 38184650) The development of novel
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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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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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youth populations. The analysis will require advanced complex sample statistical data analyses of two large population-based health surveys: the BC British Columbia Adolescent Health Survey and the Health
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available involves conducting data analyses for a project that focuses on understanding health disparities among migrant youth populations. The analysis will require advanced complex sample statistical data
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Energy Modelling and Simulation. The Dworkin group focuses primarily on numerical modelling, but also performs some experiments as needed for certain projects. The group currently has 2 Postdoctoral
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/substrate complex 3-dimensional structures in collaboration. Produce and purify functional recombinant proteins Assemble, purify and analyse the respective protein complexes Assist in the analysis
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functional genomics, CRISPR-based screening, or single-cell technologies. Hands-on experience with next-generation sequencing library prep and tissue culture models. Demonstrated ability to conduct independent