We are looking for a highly motivated individual to join the Karczewski lab in the Analytic and Translational Genetics Unit (ATGU) at the Broad Institute and MGH. We are looking for a computational scientist II with experience in large scale genomic analysis (e.g. gnomAD, multi-phenotype GWAS/RVAS). At ATGU, we build and analyze large-scale resources for biological insights and for the benefit of the wider biomedical community. The successful candidate will join an interdisciplinary team of computational biologists, bioinformaticians, software engineers, geneticists, and clinicians.
The candidate will perform large scale genetic data analyses across multiple biobanks to understand how genetic variation contributes to various disease outcomes throughout individual lifetime. Proteomics and longitudinal clinical lab values will be a specific focus in the next phase in both understanding the functional mechanisms of disease associated variants, as well as in evaluating proteins as predictors of incident disease or as biomarkers of disease progression.
The Broad Institute provides a vibrant multidisciplinary research environment with close links to MIT, Harvard, and the Harvard-affiliated hospitals across Boston. As a member of our team, you will be provided the opportunity for your contributions to be utilized and recognized across the vast global network of researchers in the fields of genomics and computational biology.
CHARACTERISTIC DUTIES:
● Lead genetics/genomics data-analysis across multiple biobanks and cohorts, developing AI systems to analyze these data
● Quality control and analysis of various omics data, especially proteomics
● Develop data-analysis pipelines for robustly and reproducibly analyze very large data sets
● Under general direction, develop innovative analytical methods to enable collaborators to interpret results and design follow-up research
● Regularly communicate accomplishments and progress at project team meetings.
● Lead and participate in preparation of manuscripts for publication, prepare reports, and present at scientific conferences.
REQUIREMENTS:
● Experience in genomic analysis of population genetics and association data. Good practical command of a wide range of tools, methods and data formats used in sequencing studies
● Ability to independently drive scientific projects from inception to publication with limited supervision
● Relevant publications in high impact scientific journals.
● Good applied statistics knowledge
● Good general programming skills and familiarity with tools of the trade (Linux, shell scripting, git etc.) are must have skills. The team currently works mostly with Python and R.
● PhD in computational biology, bioinformatics, statistics or other similar quantitative discipline or equivalent experience, and 3+ years of post-doctoral experience in statistical genetics and bioinformatics required.
● Experience with biological datasets, preferably large-scale genotyping and/or sequencing data and experience with electronic health record (EHR) are desirable
● Demonstrated capability as highly organized, a creative problem-solver, detail-oriented, self-motivated, and able to work independently as well as within cross-functional teams
● Ability to adapt to rapidly changing and high-demand environments
● Cloud computing experience (Google Cloud) and familiarity with Docker are an asset.
● Good understanding and practical experience in data management tools (sql, nosql, big data) and applications are an asset
