The unprecedented advancements in digital technology during the second half of the 20th century has produced a measurement revolution that is transforming science. In biomedical research, the Genomics revolution is being driven by new technologies that permit us to observe molecular entities analogous to identifying microorganisms and other breakthroughs permitted by the invention of the microscope. Choice examples of these technologies are next generation sequencing (NGS) and microarrays.
Scientific fields that have traditionally relied upon simple data analysis techniques have been turned on their heads by these technologies. Interpreting information extracted from these massive and complex datasets requires sophisticated statistical methodology as one can easily be fooled by patterns arising by chance or systematic errors that are hard to detect.
Rafael Irizarry’s lab is interested in the development of statistical tools that help researchers better interpret their data. The lab disseminates these tools through open source that is available for free online. This software has tens of thousands of users and the scientific publications in which these methods are highly cited.
Current projects can be dividing into the following:
If you are graduating soon with a PhD in Statistics, Biostatistics or Computer Science and are interested in the topics listed above, consider applying to join the lab as a postdoc. If you are a graduate student at Harvard you should consider doing a rotation. We don’t always have positions available but contacting us is the most common way that current members have joined the lab.
To succeed in our lab you need to have vast experience in data analysis and strong programming skills (we prefer R). Although Professor Irizarry makes time to meet each trainee weekly and the lab is highly collaborative, group members are expected to be independent.