Department of Statistics

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Research Scientist
University of Washington

Company Information: The University of Washington’s Department of Biostatistics has an outstanding opportunity for a full time Statistical Geneticist.

The Genetic Analysis Center (GAC, in the Department of Biostatistics develops and applies statistical methods to genetic and health-related data, to discover how genetic variants contribute to human well-being and disease.  The genetic data include variations assayed by whole-genome sequencing or micro-arrays, and the health data cover a broad range of traits, particularly complex diseases such as diabetes, asthma, atherosclerosis, and cancer; as well as responses to drug treatments. The projects are funded by various parts of NIH, but also non-profits and industry. Current major projects are the Trans-Omics for Precision Medicine (TOPMed) Data Coordinating and Analysis Centers ( and statistical/analytic support for the National Institutes of Health – Center for Inherited Disease Research (NIH-CIDR) program (

Position Title: Statistical Geneticist, Research Scientist 4

Duties and Responsibilities: Provide data analysis, programming, experimental design, interpretation and reporting of results for statistical genetics/genomics projects, both independently and in collaboration with other staff of the Genetics Coordinating Center (GAC). Current activities include participation in the Trans-Omics for Precision Medicine (TOPMed) project (, which is a cutting-edge initiative to identify genetic risk factors for heart, lung and blood diseases using whole-genome sequencing and other omic data, such as metabolomics and transcriptomics. The GAC is the TOPMed Data Coordinating Center, which provides TOPMed with quality control of genomic data, harmonization of clinical phenotypes and development, evaluation, application of statistical models to analyze genotype-phenotype associations and for integrating other omic and clinical data, all to understand health and disease.

The responsibilities of this position involve the following activities:

• Work with GAC faculty and staff to develop goals and strategies for data analysis and experimental design.
• Create, manipulate, and merge large and complex data sets.
• Stay informed about new methods in statistical genetics and understand how to apply them appropriately.
• Program statistical data analysis of large data sets efficiently using parallel computing locally and in a cloud environment.
• Develop, package and document software for use by GAC staff and others.
• Summarize and communicate results of analyses to GAC staff and clinical collaborators.
• Interpret results; identify potential problems and their solutions.
• Perform simulations to support statistical methods development.
Prepare results for publications, work with collaborators in writing publications and, in some cases, take the lead in writing publications. Participate in writing grant applications.

Position Qualifications: REQUIREMENTS:

• PhD and 2 years of experience in a quantitative field of science where management and interpretation of large and complex data sets was undertaken.  This training should have made extensive use of advanced computational and statistical techniques. MS and 4 years of experience with demonstrated research ability may be considered.
• Knowledge of or ability to quickly learn both the biology and statistics required for analysis of projects relating to translational, genetic, or genomic research.
• Experience in management, analysis and interpretation of large and complex scientific data sets.
• Ability to detect problems in data or analytic results and find appropriate remedies.
• Experience in statistical software packages (e.g. R, SAS, STATA, S-Plus, SPSS).
• Excellent communication skills and ability to translate complex genetic or medical research questions into statistical questions.
• Ability to write clearly and prepare results for publication.


• Ph.D. in statistics with specific experience in statistical genetics
• Publications in statistical genetics
• Advanced skills with R and Linux/Unix systems
• Experience with cloud computing
• Familiarity with reproducible research principles and tools (e.g. git, R Markdown/Sweave)

Salary Range: depending on experience

Benefits: Standard benefits are offered:



Application Information: APPLICATIONS:
Requisition Number: 143633

Please contact: Cathy Laurie (, Ken Rice (, Bruce Weir (, or Ingrid Borecki (

Contact Email:

Application Deadline: