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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 2 hours 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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, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific literature). Our
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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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data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San
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collaborative research on immune development and responses to respiratory viruses. Analyze clinical and large-scale datasets (e.g., genomic, transcriptomic, proteomic data). Design and execute experiments using
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The successful candidate will be responsible for developing computational and systems biology approaches to analyze spatial omics data and single-cell omics data (e.g., scRNA-seq, scATAC-seq, single
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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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of Freiburg, founded in 1457, belongs to the best universities of Germany. Freiburg has a large international studen body and is located in the Black Forrest with a 30-minute drive to both Switzerland and
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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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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems