Summer Internship Program
Computational research projects on whole-brain connectomes
This summer program is for students interested in computational projects for analyzing wiring diagrams of complete brains, utilizing FlyWire connectomic data. It’s open to undergraduate and graduate students, as well as exceptional high school students with strong programming and analytical skills.
Whole-brain connectomics is a young field. The datasets are large, recently published, and still only partly understood. Good ideas and analytical skills can lead to real scientific discoveries.
What participants work on
The FlyWire team will propose a few projects. Students may also propose their own projects. A good project is concrete, data-driven, and feasible for the summer timeframe. Suitable topics include graph algorithms, optimization, statistics, machine learning, visualization, interactive tools, and exploratory data analysis.
Projects should not require deep prior knowledge of neuroscience or connectomics. Prerequisites are: solid understanding of networks, graph algorithms, and data analysis, strong coding skills, effective use of AI tools, and ability to make clear analyses and visualizations.
How the program works
Students work independently or in small teams. The program starts with a virtual kickoff meeting in early June (exact date TBA). After that, we will hold virtual weekly office hours. There will also be one midpoint check-in meeting, where each student or team presents progress.
This is a lightly supervised program designed for independent work. Students must be self-sufficient, motivated, and able to make progress between meetings. The program is best for people who enjoy scientific discovery and can ask focused questions when they get stuck.
This is not a paid internship. Time commitment is up to the participants.
Successful projects may be presented to the FlyWire community after the program ends. Selected concluding presentations may happen in person at Princeton University.
What participants can gain
- Experience working with real, large-scale scientific data.
- A completed project suitable for a portfolio or paper.
- Feedback from FlyWire researchers and the FlyWire community.
- An opportunity to present results to an active research community.
Example project directions
Past FlyWire Data Challenges are useful examples of computational projects that do not assume neuroscience expertise:
- Visual Columns Mapping Challenge
- Minimum Feedback Arc Set Challenge
- VNC Matching Challenge
- Max Quasi-Cliques Challenge
Getting started
Start with the FlyWire Academy. Explore the public data in the FlyWire Codex. For videos, see the FlyWire Princeton YouTube channel.
For more background, see the lectures from the recent workshop on connectomics and brain emulation: schedule and GitHub. For a general introduction, read Prof. Seung's Connectome: How the Brain's Wiring Makes Us Who We Are.
Who should consider applying
- Students who like coding, algorithms, data analysis, and visualization.
- Students who can work independently and communicate progress clearly.
- Students interested in large scientific datasets.
Participants will be selected based on coding experience, prior projects, and proposed ideas, if applicable.
Apply
Complete this form: FlyWire summer projects signup.
Questions? Contact flywirecodex+summer2026@gmail.com.