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tissue and also conduct bioinformatic analysis of mIF and spatial transcriptomic data to help in identifying unique immune signatures of future neoplasia risk from these pre cancer lesions. In addition
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participatory analytics that integrates climate and health data, intersectional multi-level analysis of vulnerabilities, and participatory action research. A central aim is to translate lived experiences
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, focusing on atherosclerotic plaque samples collected from local hospitals in the region. Your primary responsibility will be to develop smooth muscle cell-based assays guided by single-cell spatial
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development Required Qualifications Ph.D. in Bioinformatics, Computational Biology, Systems Biology, or a related field Proven experience in the analysis of single-cell or spatial omics datasets Strong
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
), contributing specifically to the tasks done by the IST-ID team. The work will focus on creating a robust design tool that synergistically combines ray-tracing optical analysis with a 1D steady-state thermal
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join our dynamic research team. Our work focuses on craniofacial regeneration and distraction osteogenesis, using cutting-edge multi-omic approaches (single-cell and spatial transcriptomics, genetic and
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through model forests. Granular Matter, 22(1), 1–10. https://doi.org/10.1007/s10035-019-0980-9 Zhang, Y., Shen, C., Zhou, S., & Luo, X. (2022). Analysis of the Influence of Forests on Landslides in
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Cartographic Heritage to model the impact of land changes on the hydrological and river systems in Europe The main goal of this proposal is to develop strong research and analysis skills of a PhD student
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sequencing and spatial transcriptomics data. Learn and master skills for integrative analysis of high-dimensional bulk and single-cell multi-omics data. Gain rich knowledge in cancer biology, cancer genomics
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understanding and experience of cancer biology, cell and molecular biology, and biochemistry. Practical experience with bioinformatics and omics data (transcriptomics, proteomics, spatial data) and analysis (e.g