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and/or lung cancer) and flow cytometry Desirable : Previous experience in transcriptomic analysis (scRNAseq), scripting languages (R) and Seurat. Would be a plus : Previous experience in epigenetic
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experience with in vivo cancer murine models (breast cancer and/or lung cancer) and flow cytometry Desirable: Previous experience in transcriptomic analysis (scRNAseq), scripting languages (R) and Seurat
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expertise in immunology or cell biology, with solid experimental lab skills. – Experience with animal models (mouse work) and advanced immunological techniques. – Skills in RNAseq analysis (highly valued
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strong track record of research and publications. Experience with in vivo models and/or immunology (highly desirable). Skills in bioinformatic analysis (e.g., scRNA-seq) are an advantage. Ability to work
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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the laboratory: –Lefebvre A. et al. Neuroanatomical Diversity of Corpus Callosum and Brain Volume in Autism: Meta-analysis, Analysis of the Autism Brain Imaging Data Exchange Project, and Simulation. Biol
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of genetic networks Interplay between chromatin architecture and gene regulation Candidates will use a combination of skills in molecular and developmental biology, instrumentation and data analysis to answer
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Islands. NPJ Genomics Medicine. 2019 Jan 21;4:1. de Chaumont F. et al. Live Mouse Tracker : real-time behavior analysis of groups of mice. Nature Biomedical Engineering 2019 3(11):930-942. Huguet G. et al