Students who want to work in cancer research, and who are interested in learning and applying data science methods should contact me to join the lab. Our work is 100% computational, using data sets generated by other people. So, students should be excited to learn to visualize and model data sets using tools like R and Python, and packages like tensorflow/pytorch and Stan.
This research sits at the crossroads of computational biology, data science, and epidemiology, and there are a number of possible projects. Your ideas for other projects are welcome!
Please write to me sending:
PhD Students: These positions are fully funded with a mix of TAship and research funds. Students should apply to the UML Applied Biology PhD program – applications are rolling
MS Students: students should apply to the MS Biology program. As the MS program is only 2 years, students are encouraged to contact me as early as possible in your first semester.
Undergraduates: please contact me for possible projects. Students from biology, computer science, and other sciences may find good fits
I take my responsibilities as a mentor seriously, with a goal of treating students as colleagues in a collaboration. As an example of my mentoring philosophy, please check out the Statement of Expectations I created for summer research students previously.
My responsibilities involve:
The student’s responsibilities include:
I think it is important to address a common source of tension in research: the idea that only some people can “cut it”. I do not feel it is my job as a mentor to judge students’ brilliance, but only to work together on well-supported analyses using good communication. Research is hard, so project success should not be considered a reflection of your personal abilities. Please read up on impostor syndrome, something that all of us in science are prone to suffer! This problem is often more acute for people in underrepresented groups (especially including women in science and ethnic minority members).