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to high-dimensional omics datasets. Familiarity with transcriptomic analysis tools (e.g., Seurat, Scanpy, DESeq2). Experience with spatial transcriptomics and multi-modal data integration is highly
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leading role at the international level, for example in the field of plant and microbial data management, in the evaluation of new methods of genome analysis, in the integration, interpretation, and
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Foundation (FAPESP), and combines statistical analysis, spatial methods, and qualitative research. Georeferenced data from the Military Police and the Municipal Secretariat of Urban Security will be used
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defined the cell types and mechanisms that instruct peripheral regulatory T cell development and tolerance to the gut microbiota (https://www.nature.com/articles/s41586-022-05309-5 ) and identified
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on campus and beyond. At Notre Dame, your work matters, and so do you! Job Description Applicants must apply through Interfolio at https://apply.interfolio.com/182627 . Applications submitted through
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collaborative research environment to analyze unique spatial data in an innovative manner. You will develop and perform cutting-edge bioinformatic analysis integrating different multiplexed spatial data, and gain
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clustering analysis using Voronoï tessellations particle tracking and shadowgraphy measurements, will be used to quantify particle size, velocity, and spatial organisation. These experiments will be
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community; support multi‑omics data integration and analysis across multiple research groups; and collaborate on the development and maintenance of computational pipelines for spatially resolved
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the occupational risks faced by inhabitants of the Roman Empire influenced their choice of preferred cults. The main methods used in the project include spatial analysis, predictive modelling, statistics, and the
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) (Dr. Simpson’s webpage). The original call for the solicitation can be found here: https://www.energy.ca.gov/solicitations/2025-02/gfo-24-307-advancing-designs-and-analysis-high-voltage-direct-current