Houston Methodist Hospital is the flagship hospital in the Texas Medical Center, recognized by Forbes as one of ‘America’s Best Employers 2019’ in the Healthcare & Social category. The Gao laboratory at the Center of Bioinformatics and Computational Biology harbors both single cell sequencing technologies and computational methodologies under one roof. Dr. Gao has significant contributions in the development of punctuated copy number evolution model in primary triple-negative breast cancer that is a paradigm shift challenging the Darwinian Gradualism in tumor evolution (Nature Genetics, 2016), bi-mode chemoresistance evolution model where adaptive selection of genotypes and inductive reprogramming of phenotypes are activated in parallel (Cell, 2018), high throughput nanogrid single nuclear RNA sequencing method that opened the avenue of analyzing single cell transcriptomes from archival frozen tissue samples (Nature Communications, 2017) and multiple computational methods for analyzing single cell genomics data. Moving forward, Gao Lab is focusing on developing novel computational tools to integrate single cell multi-omics and establishing new experimental pipelines to perform third generation of single cell long read and spatial sequencing to unveil both somatic and mosaic genetic abnormalities that underly human cancer, vascular and muscular diseases.
We are looking for highly motivated candidates, who are interested in applying single cells genomics and quantitative skills into tumor evolution, therapeutic resistance and early detection areas, as well as developing spatial sequencing/imaging data analysis methodologies. Postdoctoral researchers will also have opportunities to pursue research interest in human cardiovascular and neurodegenerative disease using single cell genomics approaches.
Applicants must be recently graduated PH.D. or M.D./PH.D.; Degrees in Bioinformatics, Genetics and Genomics, Computational Biology, or equivalent areas are highly preferred. Interested candidates should directly send a CV along with contact information of three references to Dr. Ruli Gao (email@example.com). URL: https://ruligaolab.github.io.
Tagged as: Life Sciences
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