Tamar Melman is an experienced computational biologist currently working at Quest Diagnostics, focusing on the development of computational assays for low pass whole genome sequencing. Previously, at the Broad Institute of MIT and Harvard, Tamar led the development and validation of copy number variant annotation tools aimed at clinical applications. Tamar's experience also includes working as a computational biologist at Biobot Analytics, automating a qPCR data pipeline for early detection of SARS-CoV-2, and serving as a technical advisor and fellow at Insight Data Science, where support was provided to PhD graduates on technical and communication skills in data science. As a data scientist at ClimaCell, a customer-requested product for weather-related road risks was developed, and Tamar also contributed significantly to research at Weill Cornell Medicine and Beth Israel Deaconess Medical Center, focusing on methods to enhance data analysis efficiency in clinical settings. Tamar holds a Bachelor of Science in Computational Biology from Carnegie Mellon University and a PhD in Computational Biology in Medicine from Joan & Sanford I. Weill Medical College of Cornell University.
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