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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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Biology in Cancer Genomics and Immunology. This position will be involved in the development and/or application of computational approaches to understand the mechanism of cancer development, progression
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data, metabolomics and/or proteomics. Develops robust pipelines for data annotation, analysis, and quality control. Creates analytical algorithms and tools to address scientific questions with big data
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present their findings, and develop their own independent line of research. The ideal candidate works effectively on a diverse, multidisciplinary team and has a zest for organization and accomplishing goals
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, immune escape, and clonal evolution leading to leukemia relapse, with the goal of developing novel immunotherapeutic strategies. The fellow will have access to cutting-edge tools including genetically
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engineering, murine modeling of cancer. Designs advanced experiments and executing protocols. Documents and presents experimental results in a professional manner. Contributes to the development of a laboratory
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immunotherapy research community and publish in top-tier journals. The successful candidate will work in a diverse, collaborative environment where career development is a major priority. This position offers
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mammalian brain development, and how abnormalities in normal brain development lead to the development of brain cancers. Analyzes and interprets data (whole-genome, whole-exome, ChIP-seq and RNAseq) in light
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supervisors. Documents clinical activities. Evaluates and analyzes data independently. Establishes new research protocols and procedures. Develops service line focused on peer support services participating in
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, genetic, and immunological approaches to understand the mechanisms of cancer predisposition, initiation, and progression and to develop agents (compounds, antibodies, and vaccines). The postdocs will