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Field
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whole-genome sequencing (WGS) on microbial samples from various environments (clinical, environmental, tumor-associated microbiomes). Develop and implement bioinformatics pipelines for resistome, mobilome
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. What will I be doing? As the selected candidate, you will participate in research using a variety of molecular biology assays and bioinformatic tools to analyze malaria parasite genomes for the purpose
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developing statistical and machine learning approaches for the integration of cancer multi-omics data and the analysis of CRISPR-based screens. Responsibilities include designing bioinformatics workflows
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purifying the resulting libraries to achieve a quality compatible with different sequencing technologies. - Bioinformatic analysis of the sequence content of enriched DNA libraries. In collaboration with
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techniques such as CRISPR/Cas9 gene editing, flow cytometry, RNA sequencing, and imaging technologies. Analyze and interpret experimental data using bioinformatics/statistical tools where appropriate
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interests in tumour immunology, T cell engineering, and immunotherapy. You will join a multidisciplinary team spanning immunology, and bioinformatics, with access to advanced flow cytometry, 10X Genomics, in
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data (e.g. ITS, mtSSU); Experience in the use of molecular databases (GenBank, BOLD SYSTEMS, UNITE); Knowledge of bioinformatics applied to molecular phylogeny (alignments, phylogenetic trees, species
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spanning immunology, and bioinformatics, with access to advanced flow cytometry, 10X Genomics, in vivo imaging platforms. Key responsibilities To work within the Mansour and Roghanian labs, and with
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laboratory members with expertise in epidemiology, bioinformatics, pathology, molecular biology, and functional genomics Participate in group meetings and work collaboratively on larger projects with other
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and to develop accurate cancer risk prediction models. This role involves developing computational pipelines, conducting statistical and bioinformatics analyses, and integrating multi-omics data