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projects focused on the cancer genome in pediatric brain tumors and other malignancies. The lab is broadly interested in the cancer dark proteome and functional genomics. See prior work: Prensner JR et al
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research programmes: Comparative genomics and high-throughput functional screening to identify genotype–phenotype relationships and reveal the molecular basis of metabolic innovation. Generative AI-driven
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Biologist in the Gillani Lab in Computational Pediatric Cancer Research (https://gillanilab.dana-farber.org/). The Postdoctoral Computational Biologist will work on the analysis of genomic, transcriptomic
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-nucleus transcriptomics profiling is required. Practical experience generating single-cell or single-nucleus RNA-sequencing data using 10x Genomics or equivalent platforms, including sample quality control
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expected to conduct and advance independent research projects focused on the cancer genome in pediatric brain tumors and other malignancies. The lab is broadly interested in the molecular basis of cancer
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offers research opportunities to motivated postdoctoral fellows interested in solving agriculture-related problems at a range of spatial and temporal scales, from the genome to the continent, and sub-daily
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offers research opportunities to motivated postdoctoral fellows interested in solving agriculture-related problems at a range of spatial and temporal scales, from the genome to the continent, and sub-daily
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perform bioinformatic data analysis on proteogenomic data generated across high-throughput profiling platforms from multiple cancer types. 2) Establish a comprehensive clinico-genomic database, web resource
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biology, genomics, or mouse models. · Strong experimental, analytical, and problem-solving skills. · Excellent written and verbal communication skills with demonstrated scientific writing
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for medical imaging, precision medicine, statistical genomics, graphical models, and the analysis and integration of complex, high-dimensional biomedical data. The fellow will be expected to develop novel