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to predict precipitation fields over the Greenland Ice Sheet and the Himalaya in one combined project. For the Greenland Ice Sheet, the focus is on the spatial precipitation distribution on monthly and yearly
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samples and run immunology assays including flow cytometry, single cell sequencing, spatial transcriptomics, and high throughput immune repertoire sequencing. Manage mouse colonies, including organizing
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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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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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of neurons to become active during spatial navigation, in mice. To this aim, the candidate will investigate longitudinally - by using head-fixed two-photon imaging in combination with cellular labelling
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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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. 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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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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(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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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