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Children's Cancer Center. The Postdoctoral Associate will finish experiments, data analysis, and manuscripts related to the IL18 mediated enhancement of CAR NKT anti-tumor activity project. The ideal candidate
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field (e.g. statistics, computer science, or quantitative biology). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming
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machine learning approaches where applicable. Provides feedback and guidance to wet-lab scientists on experimental design. Summarizes research findings and publish results in research journals. Assist with
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, including in computational tasks where data visualization, preprocessing, or interpretation can be improved. Devises and deploys custom machine learning approaches where applicable. Provides feedback and
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well as bulk RNA-Seq, Proteomics, and Metabolomics generated from mouse and patient cohorts with rich clinical data - Advanced modeling of arrhythmias using generalized linear models and machine learning
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learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology, genomics, and epigenetics. Experience in next-generation sequencing data and scRNA-seq data
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are also developing novel machine learning methods to improve risk gene prediction and variant interpretation. This role will focus on the analysis of large-scale human genetics, scRNAseq, and proteomics
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models and machine learning. Minimum Qualifications MD or Ph.D. in Basic Science, Health Science, or a related field. No experience required. Preferred Qualifications Experience in epigenetics or gene