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We are looking for a computational research scientist. Computational research scientist We are seeking to strengthen our analytical team at the Charles Bronfman Institute for Personalized Medicine, at the Icahn School of Medicine at Mount Sinai with an outstanding computational research scientist, interested in the genetics and genomics of complex traits. The Charles Bronfman Institute for Personalized Medicine is an interdisciplinary institute to advance personalized health and health care. One of the institute’s key resources is the BioMe electronic health record (EHR)-linked Biobank, an ancestrally diverse population of >40,000 individuals recruited from throughout New York City. BioMe has a longitudinal design and captures and full spectrum of common and rare biomedical phenotypes. BioMe is also rich in genetic data, including genome-wide array genotypes, and exome (N~32,000) and whole genome (N ~12,000) sequencing data. Job Summary The successful candidate will manage the challenges of EHR-linked data, apply phenotypic algorithms and efficiently analyze and interpret the results. This will involve the application of variant calling and annotation software to high‐density genotyping and sequencing data (including genome‐wide arrays, ExomeChip, and next generation sequencing), as well as the application and development of approaches aimed at streamlining pipelines to deal with the analyses and interpretation of data from genetically diverse populations. S/he will integrate the increasing amount of data for further downstream analyses. S/He will lead a variety of projects and gain exposure to many productive areas of research by providing computational/analytical/bioinfornatic services for biomedical data from cutting-edge genomic technologies. The ideal candidate has a PhD in Computer Science/Statistics/Bioinformatics/statistical genetics/genetic epidemiology/computational biology or a related discipline. An understanding of biology, particularly genetics, is advantageous. S/He will have excellent programming skills (e.g. Perl or Python) and proven experience in the manipulation and statistical analysis (e.g. R) of large datasets from different sources and in different formats in a high performance computing environment, and in conducting, managing, and organizing research projects. The successful candidate will be part of a stimulating and internationally competitive scientific environment, and is expected to work closely with colleagues in the institute and the school. Salary will be commensurate with experience and NYC living costs. Duties and Responsibilities 1. Manage high-volume genotype (from microarray and whole genome/exome sequencing) and phenotype data derived from the EHR-linked BioMe biorepository. 2. conduct statistical and genomic analysis, and participate in the preparation of manuscripts and presentations. 3. Establish, maintain and streamline pipelines for data access and analysis for researchers at IPM, Mount Sinai and as part of national and international collaborations. 4. Secure data and control data access in accordance with collaboration agreements, data use agreements, IRB and PPHS requirements, HIPPA, NYS and Mount Sinai policies for privacy and data security. 5. Collaborate with Mount Sinai IT Department and High Performance Computing Group to budget, allocate and manage computational and data storage resources. 6. Collaborate with ISMMS faculty to define data requirements supporting their approved projects and direct IPM staff in the preparation and delivery of datasets to authorized individuals. 7. Supervise junior staff and/or technical/programming personnel charged with data management or computational resources. 8. Other related duties as assigned. Education PhD in Computer Science/ Statistics/Bioinformatics/statistical genetics/genetic epidemiology/computational biology or a related discipline. Previous Experience At least 5 years of experience in research environment, including 3 years, managing large datasets. Minimum of 3 years in project management role managing multiple concurrent projects. Advanced knowledge of genetics and/or statistics analysis software and online resources. Experience in programming environments such as Matlab, R statistical package, BioConductor, Perl and C++. Excellent organization and communication skills, with demonstrated ability to productively work as a member of a team. Strong verbal and written communication skills in English are required. Strong technical documentation skills are required. Experience analyzing high-throughput genomic datasets. Computer Skills Unix, statistical programming, scripting, git, wiki, database management systems. To apply, please send CV and cover letter to Stacy Paris ([log in to unmask]<mailto:[log in to unmask]>). You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.