Many undergraduates understimate the importance of research experience. If you are interested in a career in science, early research experience is instrumental in helping you reach your goals for graduate school or employment. Graduate schools and employers will look very closely at your research experience and letters of recommendation, which can make or break your application.

I am committed to providing a valuable undergraduate research experience, but I also expect you to be committed to it in return. If your goal is to just check a box or for a line item on your resume, please look elsewhere. But if you’re interested in a real-life project and are dedicated to completing a meaningful body of research, resulting in presentations and publications, then my group may be a fit for you.

Prerequisites

I am looking for dedicated undergraduates with experience or interest in both biology and computer science. Our research questions are biological, but our solutions are computational, so your skill with and interested in computer science will be key for you to succeed in my group. I expect new undergraduate lab members to have taken at least 1 computer science course, but the more experience and coursework you have completed in computer science, the better. Completing a useful research output will usually require multiple years, so ideally you will be interested in a long-term project that will build as you approach graduation. But the most important requirement is for you to be intellectually invested in your research experience.

My mentoring approach

My goal will be to develop with you a research project that fits your interests and gives you a meaningful, complete experience. I want your research to both support and complement your traditional coursework – not to be an afterthought. I want you to feel like you belong to a group that will support and help you as you face challenges in your project. I want you to finish your undergraduate experience with a research result you can showcase.

To facilitate this, after an intial phase to make sure my group is the right fit for you, I expect a commitment of at least 10 hours per week during the semester for late-stage undergraduates. I also provide and encourage opportunities for you to continue your research during the summer.

About the lab

The group (http://www.databio.org) occupies wet and dry lab space in the Center for Public Health Genomics at UVA. We are an interdisciplinary and highly collaborative group, and therefore we are also affiliated with with several other entities at UVA, including the Department of Biomedical Engineering in the School of Engineering, and Departments of Biochemistry and Molecular Genetics and Public Health Sciences in the School of Medicine, as well as the Data Science Institute and the Child Health Research Center.

Our research is at the interface of computation and biology, drawing on techniques in computer science, data science, bioinformatics, and machine learning, and applying them to biological questions in cancer, epigenetics, single-cell analysis, development, and genomics. We collect both novel data and public data for and make use of UVA’s high-performance cluster for computational approaches to biological questions.

Our biological questions are focused on understanding gene regulation and epigenetics in cancer and development. How does DNA encode regulatory networks that enable cellular differentiation? We rely on experimental data from sequencing-based epigenome experiments like ATAC-seq, bisulfite-seq, and ChIP-seq, and we use these data to study pediatric cancer, neuroimmunology, and other models to explore fundamental principles of regulatory DNA.

Teamwork is our foundation. We are trying to build a team of intelligent, creative people who are interested in working together to accomplish great things. We collaborate with other research groups extensively. We emphasize social coding, using GitHub to share code both within the group and so others can benefit from our work. Writing readable, reusable code pays off as we accumulate useful code and re-apply it to new biological systems. We challenge the norm in academic computational research of individual scientists writing isolated code, and instead push open, multi-author code development.

If these topics excite you, please read more about our research interests, recent publications, and philosophy of open data.

Next steps

If you are interested in these research topics and willing to invest substantial effort, then I’d be delighted to hear from you. Drop a note at including your year, major, availability (how much time you wish to commit), research interests, and level of computational experience.