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Responsibilities: · Develop novel statistical methods for robust pathway analsysis · Develop novel statistical methods for spatial transcriptomics data analysis · Data management · R
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from human blood and tissues) and analysis of -omics data, including spatial transcriptomics, to investigate the role of CD8 T cells in the cellular and molecular mechanisms of autoimmune diseases
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project at the intersection of RNA biology, cancer biology, and virology. Experience in molecular biology, data analysis, and tissue culture is required. The Wang laboratory is currently studying The role
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on their individualized data analysis. · Work on an organized record of dry lab scientific research with interpretable data visualizations and results in Github (e.g., using Jupyter notebook). Work Location: Onsite
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: Minimum Qualifications: Applicants must meet minimum qualifications at the time of hire. PhD in biostatistics, statistics, or related field Experience using R and/or Python to carry out data analysis
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analysis of large data sets Prior experience in signal transduction research Knowledge, Skills and Abilities: PhD level knowledge and understanding of basic cellular and molecular biology Expertise in cell
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to study leukemia pathogenesis. Analysis and Publication of Research Data (20% of Time Spent) Mentoring of students and technical staff (5% of Time Spent) Prepare data and manuscripts for publication Prepare
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. Use of animal model systems to study leukemia pathogenesis. Analysis and Publication of Research Data (20% of Time Spent) Mentoring of students and technical staff (5% of Time Spent) Prepare data and
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preliminary data, including: · Investigating the role of a key protein in regulating vesicle trafficking, with relevant biological endpoints already identified. · Exploring the differentiation
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, including design of experimental setup, data generation, data interpretation, and manuscript writing, with the following key responsibilities: Wet lab responsibilities : Conducting molecular biology