About the Program

The Master’s Degree Program in Computational Biology and Quantitative Genetics is designed for students seeking both theoretical and practical training in the quantitative analysis and interpretation of large-scale, public health genomic data.

Students will receive training in quantitative methods, including:

  • linear and logistic regression
  • survival analysis
  • longitudinal data analysis
  • statistical computing
  • clinical trials
  • statistical consultation and collaboration
  • epidemiology

Students will also gain a strong foundation in:

  • modern molecular biology and genetics
  • computer programming
  • the use and application of tools for analysis of genomic data
  • methods for integrative analysis
  • meta-analysis of genes and gene function

The program, which is typically completed within 18-24 months, requires a minimum of 60 credits of course work and a supervised 10-20 credit Collaborative Research Thesis. The thesis research will be carried out at selected research institutions where trainees will have access to mentoring by experienced quantitative scientists with expertise in the analysis of genomic data. The thesis will be presented in both oral and written form before a committee consisting of the thesis advisor and two additional program faculty.