Huggy Lab Hugging Science

Google Summer of Code 2026

Welcome to Hugging Science — part of the Hugging Face ecosystem dedicated to ML for science. Join our community building tools that enable more people to work on interesting scientific problems.

Applications open March 2026
12+ week coding period
Stipend provided

How to Apply

Follow these steps to submit a strong application. Start early — the more you engage with our community before applying, the better your chances.

01
Explore
Read through our Ideas List and find a project that excites you.
02
Engage
Join our community channels, introduce yourself, and start a conversation with mentors.
03
Contribute
Make a small contribution — fix a bug, improve docs, or submit a small feature.
04
Propose
Write and submit your proposal on the GSoC website before the deadline.

Application Requirements

Please include the following in your application:

  • A brief CV
  • What interests you most about this project?
  • What do you think will be challenging about this project?
  • What experience can you rely on to address these challenges?
  • As mentors, how can we get the best out of you?
  • Are you studying or working on anything else during the program?
  • What techniques and tools do you use to stay organized?

Project Plan & Timeline

Your proposal must include a well-defined schedule:

  • Select a project from the ideas page, or propose your own (discuss with mentors first)
  • Include a detailed weekly schedule with clear milestones and deliverables
  • For your own ideas: include outline, goals, and weekly schedule
  • List any other commitments during the GSoC period (exams, classes, holidays, jobs, weddings, etc.)
  • We can work around a lot of things — it helps to know in advance!

Join Our Community

Become a member of an awesome community working on ML for science!

  • Join the Hugging Science organization on Hugging Face
  • Connect with us on Discord
  • Read the contributor docs and developer guides
  • Ask thoughtful questions — show that you've done your homework first
  • Be respectful of mentors' time — they're volunteers
  • Participate in discussions, code reviews, and community calls

Eligibility & Expectations

Make sure you meet the requirements and understand what's expected.

  • You must be 18 years or older at time of registration
  • Open to students and beginners to open source
  • Commit to 12+ weeks of active development (175 or 350 hours)
  • Regular check-ins with your mentor (at least weekly)
  • Participate in midterm and final evaluations
  • All code must be open source under the project's license

DOs and DON'Ts

Keep these in mind throughout the application process.

  • Do start engaging with the community early
  • Do make small contributions before applying
  • Do ask mentors for feedback on your draft proposal
  • Don't submit a proposal without talking to us first
  • Don't use AI to write your proposal — we can tell
  • Don't apply to more than 2–3 orgs without genuine interest

Project Ideas for GSoC 2026

These are suggested project ideas. You're welcome to propose your own idea — just discuss it with a mentor first!

Unified MLIP Library

Large — 350 hrs AI/ML

It would be great to access MLIPs (Machine Learning Interatomic Potentials) directly from Hugging Face. This project involves creating a common Python object to describe Systems, with two main possibilities being torchsim.SimState or ase.Atoms.

Mentors: Thomas Loux (Altrove), Georgia Channing (Hugging Face)
Difficulty: Intermediate
Skills:
Python PyTorch ASE molecular simulation

Building Protein Generation Pipelines

Large — 350 hrs AI/ML

Most protein generation pipelines are built with a sequence of diffuser, folder, and then scorer. We want those to be plug and play — making it easy to swap components and build custom pipelines for protein design workflows.

Mentor: Georgia Channing (Hugging Face)
Difficulty: Advanced
Skills:
Python diffusion models protein folding pipelines

Supporting Scientific Data Types

Medium — 175 hrs

We want to be able to load FASTA, FASTQ, mmCIF, and HDF5 files quickly for machine learning. We've recently added some of this functionality, but there is so much more to be done and documentation is needed for all of it.

Mentor: Georgia Channing (Hugging Face)
Difficulty: Beginner-friendly
Skills:
Python data formats documentation bioinformatics