Undergraduates

We are actively recruiting undergraduates, especially those with a background in computer science and an interest in neuroscience, cancer biology, and/or immunology.  Undergraduates with an interest in learning computational biology techniques for cancer, immunology, neurobiology, and machine learning research are encouraged to contact Dr. Irish to learn more about opportunities.  Our work involves generation of large, complex data sets and we frequently need help with a) implementing existing data analysis tools (for those interested in e.g. bioscience & neurobiology) and b) developing new data analysis tools (for those in e.g. computer science & machine learning).

Most undergraduates in the lab will start on the neuroscience (NURO) or bioscience (BSCI) research tracks.  If you’re a biologist getting started, please check out NURO 3860 Introduction to Research in Neuroscience or BSCI 3861 Introduction to Research.  Each is followed by opportunities for independent research and an Honors thesis.  If you’re coming from a computer science or related background, you may be interested in Artificial Intelligence Research and our goal to create machine learning algorithms for biology and medicine.

Note: undergraduate projects in the Irish lab nearly always start emphasizing data analysis.  As a systems biology lab, nearly half of our research focuses on “dry lab” data analysis and computational biology.  We have found that even for undergraduates interested in clinical/translational projects, starting out on data analysis provides a great way to learn about the details of the system, contribute quickly to an ongoing project, and potentially become a co-author on a manuscript.  It is also a way to generate your own project by making an interesting new observation.  Don’t worry if you don’t know data analysis approaches — we will teach them and provide you with all the software and training you need.  After the introductory work is complete, undergraduate projects will generally align with project opportunities for graduate research.