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Natalie Stanley ’13.
Former mathematics major Natalie Stanley ’13 pursued her passions for mathematics, biology and computer science at the University of North Carolina at Chapel Hill earning a Ph.D. in computational biology. Now as a postdoctoral fellow at Stanford University, she works in their computational immunology laboratory, striving to extract interpretable data to share with immunologists.
Can you speak to how Dickinson’s useful liberal-arts education helped you along your career path?
Thanks to the diverse liberal-arts education that I received at Dickinson, I started to think outside the box and in an interdisciplinary way very early in my education. Currently, I work at the intersection of three fields (immunology, computer science and machine learning) and knowing how to communicate with people with different backgrounds is very important. As a scientist, strong writing skills are also crucial since we spend a lot of time writing papers and grants.
What was your favorite activity/organization at Dickinson?
What jumps out as a great memory from your time at Dickinson?
As a student I spent a lot of time in Tome and Rector, both studying and hanging out with friends. There was a very strong sense of community and collaboration among students in the sciences. I had an amazing time. I still keep in touch with many of these friends today.
How do you stay involved with Dickinson?
I keep in touch with many friends and faculty. I have not made it to an Alumni Weekend yet, but I look forward to attending one sometime soon!
How did you get interested in your work, and what about it excites you most?
I came to Dickinson wanting to major in biology to ultimately become a medical doctor. However, I took a few math courses, and, after linear algebra in particular, I knew that is what I wanted to do. As a first-year, I started talking with Professor of Biology Mike Roberts and Associate Professor of Mathematics Jeff Forrester about working with them on a cancer genetics project. Combining my background in math with a strong interest in biology, this collaboration was a wonderful fit and sparked my interest in computational biology. It was very clear to me by my senior year that I wanted to pursue a Ph.D. in computational biology. That is exactly what I did.
My favorite part of my job as a computational immunologist is that the work is extremely collaborative and always new and exciting. Working with diverse teams of people, we can make predictions about particular biological mechanisms that are implicated in important translational applications. Also, at the end of the day, I love math and computer science. A lot of my work requires developing new algorithms for analyzing and interpreting complex biological data. I feel challenged and inspired to learn new things every day.
What does your current work entail?
I am a postdoctoral fellow at Stanford University. I work in a computational immunology laboratory, where we use a high-throughput, single-cell immune profiling technique called mass cytometry to understand how diverse pieces of the immune system work together in several translational applications. We develop novel machine-learning algorithms to extract information from these data and to generate interpretable conclusions that can be communicated to an immunologist. I think that for anyone who likes computer science, math and biology, this is the perfect career. I get to think about all three areas daily. I spend most of my time writing code, writing papers and grants, and mentoring students.
What comes to mind as something unforgettable that you’ve done since you graduated?
In 2018, I defended my Ph.D. at the University of North Carolina at Chapel Hill. This was an incredibly happy day that I got to share with my closest friends and family. As I developed into an independent scientist, I realized that a career in research and education is exactly what I want to do. Currently, I am preparing for a career as an assistant professor. I am very happy and grateful for the education at Dickinson that made all of this possible.
Published April 8, 2020