Biostatistician, Department of Genome Sciences

Overview

The Department of Genome Sciences at the University of Virginia School of Medicine seeks a Biostatistician. The Biostatistician will work in the lab of Dr. Ani Manichaikul on statistical analysis of human genetic and molecular 'omics studies. Analytical responsibilities will include analysis of genomic, proteomic and metabolomics data, bulk and single-cell transcriptomics data, quantitative trait locus mapping of gene expression, protein and metabolite measures, and integrative genetic analysis of common and rare disease variants.

Collaborative efforts will include an emphasis on post-GWAS studies including whole genome sequence analysis, targeted analysis of candidate genes, and integrative analysis of genomic and transcriptomic data in studies of heart failure, chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, cardiovascular disease, and atherosclerosis.

• Write Statistical Computer Programs with R or Python
• R or Python:
  • Enhance data visualization for interpretation of molecular  omics analysis
  • Conduct data automation and reporting, including:
    Develop automated data input workflows in R, enabling integration of future data into tables and figures without requiring manual code modifications;
    Create codes to looping structures to extract /display data summaries;
    Build downloadable report tables with R/Markdown and PDF export options, allowing users to save structured data directly from HTML reports;
    Enhance HTML report usability by creating scrollable tables, ensuring optimal viewing and navigation within web-based reports
  • Generate reports in PowerPoint (PPTX) & HTML formats for different presentation and sharing needs
• Review statistical analysis output for consistency & quality
• Research projects:
  • Expression quantitative trait locus (eQTL) mapping for RNA-seq data from heart failure cases and controls
  • Integration of eQTL with genome-wide association study (GWAS) data to identify molecular mechanisms underlying GWAS loci
  • Calculation and interpretation of polygenic risk scores in the context of selected GWAS and Mendelian genetic loci for heart failure and related diseases
• High performance computing (HPC) to analyze large-scale data sets
• Write methods and results sections of reports & publications
• Develop statistical designs, power calculations, and planned analyses for research grant proposals
• Develop & implement new innovative procedures in data collection, quality control, presentation of results, & statistical analyses
• Prioritize tasks
• Work independently to perform programming, select methods, and ensure quality of work
• Other duties as assigned

Education:

Master s degree

• Education:
  
  Master s or higher degree in Biostatistics, Genetics, Epidemiology, or a related field with substantial coursework in the field(s) of interest
• Experience with statistical software (R or Python); a strong work ethic; the ability to work independently combined with willingness to work in a highly interactive and collegial group; and excellent written and oral communication skills. Additional desired qualifications include experience working with large-scale multi-center studies; working knowledge of existing tools for genetic analysis and data management;
  Unix shell scripting; and experience working in a Unix / Linux environment

This is primarily a sedentary job involving extensive use of desktop computers.

The anticipated hiring range is $75,000-$90,000, commensurate with education and experience.

This is an exempt-level, benefited position. Learn more about UVA benefits.

This is a restricted position, which is dependent on funding and is contingent upon funding availability.

This position is based in Charlottesville, VA, and must be performed fully on-site.

To learn more about UVA and the Charlottesville area, visit UVA Life and Embark CVA.

Application review will begin after January 31, 2025.

Background checks and pre-employment health screenings will be conducted on all new hires prior to employment.

Please apply online, by searching for requisition number R0079983. Complete an application with the following documents:

• Resume
• Cover Letter

Upload all materials into the resume submission field. You can submit multiple documents into this one field or combine them into one PDF. Applications without all required documents will not receive full consideration.

Internal applicants: Search and apply for jobs on the UVA Internal Careers website.

Reference checks will be completed by UVA's third-party partner, Skill Survey, during the final phase of the interview. Five references will be requested, with at least three responses required.

For questions about the position, please contact Ani Manichaikul, am3xa.

For questions about the application process, please contact Jessica Russo, Senior Recruiter, sxv9zv.

The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans…