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to lead impactful research at the interface of aging biology, neurodegeneration, and spatial omics. The successful candidate will contribute to high-profile projects investigating the cellular and molecular
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an industry partnered project for translational drug discovery. The role will involve analysing large scale omics and spatial datasets from both primary patient samples and advanced in vitro model systems
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semantics and spatial reasoning. AI for Physical Systems – Leveraging machine learning and AI to improve performance, safety, and adaptability of robots, autonomous vehicles, and other intelligent machines
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an industry partnered project for translational drug discovery. The role will involve analysing large scale omics and spatial datasets from both primary patient samples and advanced in vitro model systems
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with R, statistical and spatial analysis Excellent communication and teamwork skills Excellent organizational skills Experience with field work in post-disturbance forest conditions (desired) Experience
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. You have a background in machine learning for spatial data (e.g., random forest, neural networks) or are open acquiring these skills. You have experience with handling large geospatial datasets and
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(TMJ) degeneration and pain, and salivary gland degeneration. The lab uses mouse and human iPSC/organoid models equipped with genomic, single cell RNA sequencing, spatial transcriptomics, tissue clearing
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they would design, organize, and conduct advanced quantitative (statistical, spatial, etc.) analyses relevant to climate equity, environmental justice, and/or environmental health; translate complex data and
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 2 months ago
increasingly utilizes big data, satellite imagery, register data, and advanced methods such as deep learning and neural networks to address major societal challenges related to spatial inequalities and
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for improving the environmental impacts of wood production over broad spatial scales. Required Skills and Qualifications: PhD in a forestry- or conservation-related discipline. Strong background in field survey