The Columbia University in the Department of Neurology is recruiting a scientist that will develop family and population-based methods to analyze omics data including those the implement data from a variety of sources. These methods include: rare variant aggregate association analysis to detect gene x gene and gene x environmental interactions; generalized linear mixed models for large scale variant studies to analyze family and population-based data; RNA-Seq imputation and analysis for family data; Bayesian, trans-ancestry and functional annotation for fine mapping; and analysis of imputed variant data. Develop software implementing Spark and GPUs for large scale epidemiological studies which implement these newly developed methods as well as established ones. Apply newly developed methods to study a variety of neurological traits to elucidate underlying genetic etiology. Mentor post-doctoral students and predoctoral fellows. Prepare manuscripts and presentations.
See full posting here: https://pa334.peopleadmin.com/postings/3511