This position is within a research group conducts cutting-edge research on the ways that genetic, epigenetic, and social factors influence age-related chronic diseases. We focus on identifying genes and environments that contribute to cardiovascular disease, hypertension, dementia, and their risk factors. We are seeking a Research Area Specialist Intermediate to participate in study design, analyze data from large multi-ethnic cohort studies, and write manuscripts describing the results. This position will be centered on developing pipelines for data cleaning and analysis, performing high-dimensional genomic and epigenomic analysis, drafting manuscripts, and presenting research findings.
Implement analysis strategies to perform high-dimensional genetic, epigenetic, and epidemiological analysis of large population studies.
Perform regular maintenance of datasets including merging files, restructuring and recoding variables, and checking for errors.
Create and maintain clear and organized documentation of the “workflow” and steps involved in data management and analyses, as well as well annotated program files (e.g., R code) to ensure full transparency and reproducibility.
Write methods and analysis sections for working papers, reports, and manuscripts for submission. Work with team members to draft introduction and discussion sections, and prepare manuscripts for publication. Collaborate in the development of posters and data presentations for conferences and workshops.
Develop, prepare, and implement research plans to attain specific aims of multiple research projects. Formulate research methods, identify potential problems, and recommend solutions for improving quality and efficiency.
Master's degree with 4-5 years experience in Statistical Genetics, Biostatistics, Bioinformatics, Genetic Epidemiology. Programming experience in R. Working knowledge of Unix/Linus file system and environment. Highly motivated and organized, with excellent multi-tasking ability and record-keeping. Must be able to work independently and as part of a research team.
PhD preferred. Experience with genetic analysis of large health science databases or studies. Prior experience with genome-wide analysis using R, PLINK, SNPTest, and METAL software; gene-level analysis using R packages (SKAT, MetaSKAT, etc); gene-level GxE interaction analysis using R packages (iSKAT, etc); methylation data cleaning and analysis using Bioconductor packages (Limma, ComBat, etc) and R packages (e.g. high-dimensional mediation methods), and/or gene expression data cleaning and analysis. Analysis experience in SAS, Python or other programming languages. Demonstrated interpersonal skills and oral and written communication.
This position is term-limited for one year beginning with the start date of the appointment.
The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act.
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.