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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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. The student is expected to learn to design research questions and hypotheses, design experiments, analyze data, take courses, write scientific manuscripts, communicate science to their peers and the general
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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include: Design, implementation, and benchmarking of computational pipelines for spatial and single-cell multi-omics analyses Analysis and interpretation of large-scale datasets from up to 300 CRC cases
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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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of LNPs under various storage conditions, the aim is to develop formulations with both high performance and improved stability. The work includes the design and systematic screening of LNP formulations