We seek a candidate who can apply statistical genetics knowledge and methodologies for better interpretation of human genetic data. He/She should be keen to apply state-of-the-art analytical methods to explore how genetics play a role in causing human diseases. The goal is to develop a refined genetic understanding for disease etiology/mechanism and maximize the value of human genetics through use of largescale sequencing data. One core area of research will be to systematically explore and perform analyses of a highly consanguineous population to identify human knockouts. This person will be responsible for performing data management and analyses of a large-scale genetic and biomarker data involving > 100,000 participants. He/She will conduct statistical analyses, data cleaning, data manipulation, survey data scoring, write-ups of analyses and production of tables and graphs for manuscripts and proposals.
Conduct analyses on large scale genetic datasets and conduct annotations to identify functional versus non-functional variants.
Identify human knockouts through use of statistical methods.
Use raw sequencing data to generate VCFs.
Contribute to the developing science of drug target identification and genetic validation.
Systematically apply statistical methods that integrates genetic association strength with functional annotations and explore underlying biology/potential causal mechanism(s).
Analyze public and internal datasets to explore how diseases share common genetic risk profiles.
Identify and explore how genetic factors contributes to disease susceptibility through relevant endophenotypes, and discover dysregulated pathways.
Test causal relationships between biological processes (genetics and biomarkers) and clinical outcomes using mendelian randomization framework.
Perform genetic analyses, interpretation and communication of large-scale human genetic and phenotypic data.
Use advanced programming skills on cloud computing platforms to conduct data cleaning, provide and regularly update study reports, provide descriptive and analytical reports, and perform exploratory and specialized statistical analyses and statistical modeling.
Train other bioinformaticians working on the project.
Present data at scientific conferences and publish in peer-reviewed journals.
Utilize datasets that are publicly available (GWAS meta-analysis datasets from UKBIOBANK).
Perform other related duties as required.
Bachelor's degree in statistical genetics, human/population genetics, genetic epidemiology, biostatistics or other related analytical fields, plus four years of related experience.
Master's and/or PhD degree in statistical genetics, human/population genetics, genetic epidemiology, biostatistics or other related analytical fields.
Proficiency in at least one programming language (ideally Python or R), experience in statistical methods and data modeling in high-dimensional human genetics/genomics environment.
Ability to work with others in a collegiate and collaborative environment.
Must successfully complete systems training requirements.
Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.
Internal Number: 510360
About Columbia University
Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.