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. Experience in the analysis of single cell RNA-sequencing and spatial transcriptomics data is advantageous, and proficiency in statistical analysis tools such as R or Python is desirable. Interested candidates
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, to improving research efficiency through robotics and AI, to spatial information analysis of imaging and spatial omics data, and to designing proteins. We are looking for someone who thinks beyond
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Climate Science, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in hydro-climate studies. Strong background with GIS tools and spatial analysis
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data analysis with passion and technical know how. In the role of Data Analyst, you are a central component of Prof. Nicolas Gompel's team, which investigates the genetic origin of evolutionary changes
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of the project is to develop a platform for 3D biomedical image analysis utilizing artificial intelligence, extended reality, and spatial computing. The platform should offer a user-friendly workflow through (semi
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Learning Objectives: Learn and master skills for in-depth profiling of single-cell sequencing and spatial transcriptomics data. Learn and master skills for integrative analysis of high-dimensional bulk and
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the following key areas of Single-Cell RNA Sequencing-Based Cellular Phenotyping, Spatial Transcriptomics Analysis, Single-Cell Epigenomics Analysis, and Semantic Knowledge Graph Representation. Recent advances
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diagnosis and prognosis. Our work emphasizes the use of advanced mass spectrometry (including single-cell and spatial proteomics) techniques for proteomics, protein/peptide characterization, and the analysis
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university degree (doctorate) in the fields of inflammation biology /immunology. Expertise in state-of-the-arts methods of multidimensional analysis at the cellular level (for example, spatial transcriptomics
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specialized in multi-omics technologies. Its focus extends to providing cutting-edge services in single-cell and spatial multi-omics analysis, as well as long-read sequencing. This Unit closely collaborates