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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 2 months ago
samples such as serum/plasma, biopsies and whole blood for analysis and large databases, which include clinical information on patients. The group’s homepage: https://www.skane.se/en/about-us/research/for
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Large-scale and in-depth characterization of optimized Channelrhodopsin variants for basic research in neuroscience and future optogenetic therapies Automated (Syncropatch384, Nanion) and manual patch
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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex
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supervise cutting-edge interdisciplinary research building on the analysis of large-scale blockchain data. This will include, but is not limited to: Designing, implementing, and maintaining scalable pipelines
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RNA-seq data for testing and validation. Perform data analysis on large-scale RNA-seq data in pediatric cancer. This may involve the analysis of both scRNA-seq, bulk RNA-seq as well as new single-cell
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Framework (RDF). enables advanced data mining queries using the SPARQL query language. provides a natural language-based interface to perform these queries on the knowledge graph using a large language model
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research environment, comprising two full professors, one associate professor, one assistant professor, one postdoc, and a large number of PhD students. The project includes strong partnerships with
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of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts are supported by
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large-scale whole genome and whole exome sequencing, RNA-seq, ATAC-seq, proteomics, and metabolomics data in a well-established cohort of childhood cancer survivors with clinically ascertained deep
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causal networks that govern cellular behavior from large-scale single-cell datasets. Our group has pioneered computational approaches for: Inferring causal networks from Perturb-seq (interventional single