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of antibodies/ADCs and small molecules. We are addressing combinatorial target identification with CRISPR functional genomics and chemical biology for targeting hard to treat cancers. The Aparicio Lab has a long
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genomic approach to profile enhancer dependencies. Develop and optimize experimental workflows integrating scRNA-seq, scATAC-seq, and other single-cell omics. Interpret high-dimensional data in
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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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repertoires within the thymic niche. Identify molecular and signaling targets to guide the engineering of functional thymic environments and optimize T-cell output from pluripotent stem cell-derived progenitors
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the thymic niche. Identify molecular and signaling targets to guide the engineering of functional thymic environments and optimize T-cell output from pluripotent stem cell-derived progenitors. Automate
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. David Granville, the incumbent will be responsible for: Designing and implementing research plans and approaches, including in vitro studies, in vivo models, formulation optimization Facilitating other
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, formulation optimization Facilitating other projects in the laboratory If successful, playing a key role in the establishment of a new UBC spin-off company working with programs offered through UBC and
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: Computer Architecture Algorithms and Optimization Health Research Human-Computer Interaction Machine Learning and ML Foundations Machine Perception Natural Language Processing (including Information
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partners. In these research projects we studied new diagnostic tests, therapies, service models, and technologies to optimize the physical and mental health of Canadian children born with brain-based