University of Colorado-posted 5 days ago
Full-time
Hybrid • Aurora, CO
11-50 employees

The Department of Medicine, University of Colorado School of Medicine and Department of Biostatistics and Informatics, Colorado School of Public Health is seeking a post-doctoral fellow for a two-to-three-year position studying causal inference, available to start immediately. The focus of this position will be the development and implementation of novel statistical and computational methods motivated by potential applications to observational studies. The work will involve both methodological research with biostatistics faculty and collaboration with clinical investigators. The incumbent will report directly to Dr. Debashis Ghosh, Professor of Biostatistics and Informatics, and Dr. Sridharan Raghavan, Associate Professor of Medicine. The University of Colorado Anschutz Medical Campus is a highly collaborative campus, and the particular collaborative direction will depend on the interests of the applicant. Please be advised that this position is not eligible now or in the future for visa sponsorship.

  • Data management
  • Statistical methods development
  • Exploratory data analysis
  • Bioinformatics analysis
  • R package development
  • Presentations at conferences
  • Manuscript preparation
  • PhD/ ScD from an accredited college or university in statistics, biostatistics, computer science or related field
  • Experience in causal inference
  • Minimum of 2 years’ experience in statistical software R, Python or equivalent
  • Excellent communication skills (written and oral) using the English language
  • The ability to work independently on data analysis and research
  • Ability to establish and maintain effective working relationships with employees at all levels throughout the institution.
  • Outstanding customer service skills.
  • Experience with development of R packages or other software
  • Minimum 1-year experience in machine learning methods
  • The University of Colorado offers a comprehensive benefits package.
  • generous leave
  • health plans
  • retirement contributions
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