Education

 Training in Quantitative Genomics

Groundbreaking research and discovery in the life sciences in the 21st century are more interdisciplinary than ever. To expedite scientific advances in the “omics” era, it is critical to provide the next generation of quantitative health science students with training in the areas of biostatistics/statistical genetics, computational biology, molecular biology and genetic epidemiology.

Masters Programs

The Master of Science programs train students in the basics of statistical theory, biostatistical and bioinformatics methods in planning studies, conducting analyses, and writing reports, the interpretation of numeric data for scientific inference in studies in medicine and public health, and the ability to collaborate and communicate effectively with scientists in related disciplines. Application areas include observational studies, clinical trials, computational biology and quantitative genomics, health data science, statistical genetics, and medical and public health research, among other areas.

PhD Program

The PhD program is designed for those who have demonstrated both interest and ability in scholarly research. The department’s program is designed to prepare students for careers in the theory and practice of biostatistics and bioinformatics, and includes training in the development of methodology, consulting, teaching, and collaboration on a broad spectrum of problems related to human health, genomics, and basic biology.

Training Grants

Learn more about the training grants that support the PhD Program.

Courses

Browse the courses in genetics and genomics for students interested in quantitative genomics.

Course List

HarvardX Online Courses

Created by world-renowned experts and top universities, XSeries are designed to provide a deep understanding of key subjects through a series of online courses. Developed by Dr. Rafael Irizarry, these HarvardX courses are divided into two series.

Data Analysis for Life Sciences provides the tools to analyze and interpret life sciences data. You will learn the basic statistical concepts and R programming skills necessary for analyzing real data.

Genomics Data Analysis focuses on Bioconductor and how it is used to analyze high-throughput data with a focus on next generation sequencing.