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and sample tracking into reproducible end-to-end pipelines. Develop and apply computational pipelines for image processing, cell segmentation, debarcoding and spatial statistics. Close the experimental
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Resonance Imaging to Molecular Signatures: Generative AI for Virtual Biopsy in Gliomas - Gliogen X will be to develop a non-invasive virtual biopsy based on magnetic resonance imaging to molecularly classify
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analysis, discussion of results and proposal of new experiments and approaches. He will be asked to obtain and analyze optical and confocal microscopy images and to develop radiochemical and immunochemical
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analysis, computer vision, or machine learning, with a clear interest in developing image analysis algorithms and an affinity with medical topics. Good communication and organizational skills are essential
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Website https://seuelectronica.urv.cat/treballar-a-la-urv/pi26031english.htm Requirements Research FieldChemistryEducation LevelPhD or equivalent Skills/Qualifications PhD in Chemistry, Nanoscience
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resistance. We developed synthetic cells that fight bacteria using a biomimetic form of artificial phagocytosis, a process to date only observed in living organisms. These phagocytic synthetic cells (PSCs
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cell culture models. Experience with in vivo imaging. Competencies and Skills: We value not only technical expertise but also the demonstration of core competencies such as Communication, Teamwork and
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, or 3D cell culture models. Experience with in vivo imaging. Competencies and Skills: We value not only technical expertise but also the demonstration of core competencies such as Communication, Teamwork
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cytometry, MACS and FACS, and confocal/immunofluorescence imaging of normal and leukemic hematopoietic cells and tissues. • Prepare samples and libraries for single-cell RNA-seq, spatial transcriptomics, and
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that subsequently recruit decay factors. In our lab, we investigate a distinct, newly emerging paradigm of gene regulation termed “peptide-mediated mRNA decay” (PMD). In PMD, not the mRNA sequence but rather