[R-jobs] Data Analyst in Statistical Genetics

DAVID M LEVINE |ev|ned @end|ng |rom u@w@@h|ngton@edu
Sun Dec 22 19:09:55 CET 2013

Our group in the Biostatistics Department at the University of Washington is currently seeking a data analyst to work on projects with genetic data. Our computing
environment is almost exclusively R and we have developed several R and BioConductor packages.

Position Description: The Department of Biostatistics of the University of Washington, through the Center for Biomedical Statistics and the Genetics Coordinating Center, is engaging in an increasing number of analyses of genetic data, mainly from human population samples. These data sets include whole-genome sets of single nucleotide polymorphism data from microarrays and next-generation sequencing, as well as a variety of phenotypic traits of medical importance. All of these data sets are characterized by large size and complex interaction structure. The position requires care, efficiency and resourcefulness in the management of these data, in applying new methods of statistical analyses and in interpreting results. This requires exceptional computational and statistical skills. Specific knowledge of
statistical genetics is desirable, but not essential. The specific projects generating the data change from time to time but they usually address issues of human health: either the causes of human disease or the causes of response to pharmaceuticals. The projects are from academic, non-profit and industrial institutions.

Key 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 (GCC). These responsibilities involve the following activities:
- Create, manipulate, and merge large and complex data sets
- Work with GCC faculty and staff to develop goals and strategies for data analysis and experimental design
- 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 and other resources
- Develop, package and document software for use by GCC staff and others
- Summarize and communicate results of analyses to GCC staff and clinical collaborators
- Interpret results; identify potential problems and their solutions
- Prepare results for publications, work with collaborations in writing publications and, in some cases, take the lead in writing publications.

Requirements: MS or (preferably) PhD and 4 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.

- Knowledge of or ability to quickly learn both the biology and statistics required for analysis of projects relating to translational, genetic, or genomic research.
- Ability to detect problems in data or analytic results and find appropriate remedies
- Experience in statistical software packages (e.g. SAS, R, STATA, S-Plus, SPSS) and knowledge of or demonstrated ability to learn specialized software packages for the
analysis of genetic and genomic data.
- 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

Desired: Experience in management, analysis and interpretation of large and complex scientific data sets.

For further details see UW Req# 100529 (https://uwhires.admin.washington.edu/eng/candidates/default.cfm?szCategory=jobprofile&szOrderID=100529)

David Levine (levined using uw.edu)

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