Job Title: Scientist – Statistical Genetics
A Statistical Geneticist position is available at the VA’s Center for Data and Computational Sciences (C-DACS). The center boasts a diverse team of researchers including Geneticists, Data Scientists/Managers, Software Engineers, Biologists, Clinical Informaticians and Bioinformaticians/Computational Biologists. One of the primary responsibilities of the center is generation, curation, QA/QC and integration of genomic data with clinical, self-reported and other health data in the Million Veteran Program (MVP) and Cooperative Studies Program (CSP) studies. Currently MVP has banked over 800,000 samples and generated genotype array and whole genome sequence data from over 650,000 and 150,000 samples respectively, besides generating other Omics data like methylation, metabolomics and proteomics.
Responsibilities of this position include evaluation and application of cutting-edge approaches to genome wide association studies (GWAS), analysis of genetic diversity in the veteran population, development and use of risk prediction algorithms, WGS analysis including rare-variant analysis, and support for or participation in large-scale clinical/translational research projects. We seek an individual with interest and experience in analyzing and interpreting human population genetic data. A strong background in mathematics and statistics is required.
The successful candidate will have the opportunity to contribute and lead population genetic analysis projects in the largest genomic cohorts associated with clinical/health record in the world.
The position is remote eligible.
· PhD or equivalent experience in statistics, genetics, bioinformatics, biostatistics, computational biology, data science or related field.
· Experience analyzing and interpreting human population genetics data is a must. Familiarity with the analysis of large biobank data is a plus
· Proficiency with R, Perl/Python in a Linux environment is essential.
· Knowledge and experience with statistical methodologies and principles currently used in the field of advanced population Genetics.
· Proven ability to work independently and in team environments.
· Scientific curiosity in continuous learning of biological systems, statistical methodologies, and programming skills.
· Excellent analytical and problem-solving skills.
· US Citizenship required.
· Experience in interrogation of Electronic Medical Record (EMR). Experience with Natural Language Processing (NLP) tools and algorithms is a plus but not necessary.
· Working knowledge of generalized linear models, mixed models, nonlinear models, longitudinal data modeling techniques, missing data models and non- parametric modeling.
· Familiarity with Next Generation Sequencing analysis, alignment, and variant calling.
Interested individuals should send their resume and a cover letter to Saiju Pyarajan at firstname.lastname@example.org