Do you wonder how cancer researchers use computational tools in their search to prevent cancer and find cures?
Computational skills are increasingly important in nearly all fields of biomedical research at the Hutch and beyond. Coding for Cancer connects students with computational biologists, teaches hands-on skills, and show how coding and computational tools are used in cancer research. No prior coding experience is necessary. Participants will receive a $1000 award upon completion of the program. Participants will also receive a Credly badge to showcase the work they do during the program to learn the R coding language.
This program is a collaboration among science education staff and scientists who are active computational biology researchers.
Application Process
The application for the 2025 Coding for Cancer Program is now closed. We are in the process of application review.
The application must be submitted by 11:59 p.m. PT on March 30th, 2025. Recommendation forms will be due by 11:59 pm PT on April 6th, 2025. Please apply early. View a PDF preview of the application. Do not fill out the preview PDF, it will not count as an application submission.
Note: Our programs rely on federal funding from NIH (specifically the National Institute for General Medical Sciences and National Cancer Institute) and budget support from Fred Hutch Cancer Center, both of which face uncertainty and potential cuts.
At this time, we are uncertain whether we will receive sufficient funding to hold our programs as planned this summer. While we hope to proceed in some capacity, changes such as reduced participant numbers may be necessary. As a result, acceptance decisions may be delayed beyond the previously published date. We appreciate your patience and support as we navigate this challenging situation.
Applicants Should
- Be entering 11th or 12th grade in the fall.
- Preferably live in Washington state.
- Be available for all of the program dates.
- Apply even if they have no coding experience.
This course will teach the R programming language and environment. The program will accommodate a range of prior knowledge, including those with no coding experience. We will work with students who do not have access to technology to gain the necessary equipment and internet for the duration of the program. Students will receive a $1000 award upon completion of the program.
The program is open to all students. We especially encourage applications from individuals furthest from opportunity, as described by NIH's Notice of Interest in Diversity.
Details
When: Monday - Friday, July 28th - August 22nd, 2025 from times 1-3:30 p.m. (with optional office hours 3:30-4 p.m.).
The first half of the program will have small-group and individual activities to learn the coding language and some cancer biology. The second half of the program will be focused on each students' research project.
Where: 100% virtual.
Why: You’ll have fun, learn a coding language, do hands-on activities, and meet great people!
How: Submit an application online. For the 2025 session, we have added a short Recommendation Form that your recommender/reference will be asked to submit on your behalf. We recommend students look over the Application Preview PDF before starting the application. Please do not fill out the Application Preview PDF, it will not count as an application submission.
Program Team
Mackenzie Johnson
Lead Instructor
Mackenzie is a postdoctoral fellow in Computational Biology at Fred Hutch. As a computational biologist, she develops tools to better understand the adaptive immune system, creating software to model the natural evolution of antibodies. This work aims to understand the body’s response to pathogens and provide scientists with tools to design better treatments. She completed her PhD at the University of Texas at Austin in Ecology, Evolution, and Behavior where she used statistical and machine learning models to study evolutionary biology. In her free time, she enjoys camping, crafting, and rowing.
Matthew Chan
Lead Instructor
Matthew is a postdoctoral fellow at the Fred Hutch Cancer Center. His research involves using biophysical, genomic, and computational techniques to investigate protein structure and dynamics and its implication to human diseases. He obtained his Ph.D. in Chemical Engineering from the University of Illinois where he did his graduate research in computational biophysics and molecular modeling. Outside of the lab, he enjoys playing piano, badminton, and biking.
Coding for Cancer is made possible in part by Pathways to Cancer Research (R25CA221770), a Youth Enjoy Science Award (YES/CURE), from the National Cancer Institute (NCI)