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Field
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fundamental molecular biology techniques (such as gel electrophoresis, Western blotting, qPCR, molecular cloning, CRISPR editing, plasmid construction, virus packing, iPSC culture, RNA-sequencing, multi-omics
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staining and confocal imaging, RNA-seq. Data analysis, interpretation of experimental outcomes, and preparation of manuscripts for publication Supervise and train junior researchers and contribute
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(including single-cell RNA-seq and spatial transcriptomics data). Use computational tools and algorithms written in one/all R, PERL and Python. Contribute to project management, presentations and publications
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of single-cell RNA-seq, bulk RNA-seq, and other high-dimensional omics datasets. Design and implement analytical pipelines for data preprocessing, quality control, normalisation, clustering, differential
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QTLomics as part of the project. Main responsibilities Collect and standardise functional information, including QTL data, RNA-seq, and Gene Ontology (GO) annotations Develop computational pipelines for QTL
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animals and researching lung comorbidities in HIV, as well as experience and publications demonstrating analyses of omics data, including RNA-seq, single-cell genomics, spatial transcriptomics, and
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: protein biochemistry, enzyme kinetics, coagulation assays, recombinant protein expression ● Molecular biology: gene expression analysis, RiboTag/RNA-seq, CRISPR, cloning ● Cell biology
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. Qualifications Preferred Skills Analysis of shotgun metagenomics sequencing and metabolomics data Integration of single-cell RNA-seq with proteomic and metabolomic datasets Application of machine learning and AI
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Data Analysis Center that manages multi-omic data (e.g., Illumina/PacBio/ONT Whole Genome Sequencing (WGS), RNA-Seq). The ideal candidate will have a deep understanding of next-generation sequencing (NGS
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/Cas9, single cell RNA-seq, cell culture with live cell imaging, immunohistochemistry with confocal microscopy, Ca2+ imaging, coimmunoprecipitation and proteomics. IUSM is committed to being a welcoming