Unlock Funding and Compute for Your ML Research!
Google has officially announced its 2026 Awards for Machine Learning Research and Education with TPUs! This is an incredible opportunity for our lab members to secure significant funding and top-tier computing power.
Google is inviting proposals to advance machine learning through foundational research, applied science, and the integration of Google TPUs into educational courses.
What is the Award?
Selected proposals will receive a fantastic support package:
- Unrestricted Gift: Funding ranges from $25,000 to $100,000 USD. This is primarily intended to support graduate students or faculty members.
- Free Compute Resources: Access to the latest generation of TPUs via Google Cloud, with allocations customized for your project.
- Technical Mentorship: Direct access to Google’s product and engineering teams for guidance and troubleshooting.
- Google Cloud Credits: Additional credits to support your cloud infrastructure.
Who Can Apply?
- Faculty Members: The awards are open to faculty at degree-granting universities globally.
- PhD Students: Yes, PhD students are highly encouraged to apply! You simply need to include a faculty supervisor on your application.
Award Tracks
Google is accepting proposals across two main tracks:
Track 1: Research Awards
This track focuses on accelerating research across various domains:
- Theme 1: Foundational ML: Pushing the boundaries of ML performance and scalability. This includes ML Systems, Distributed Systems, and Model Innovation.
- Theme 2: Applied Science: Utilizing high-performance computing for discoveries in Healthcare & Life Sciences, Climate & Crisis Resilience, Accessibility, and Computer-Aided Engineering.
- Theme 3: Open Source Contributions: Developing foundational tools, systems, and models (like Tunix, MaxText, or custom kernels) that benefit the broader TPU developer community.
Track 2: Education Awards
This track aims to integrate TPUs into university curricula:
- Focus Area 1: LLM & Systems Courses: Curricula covering Large Language Models, Distributed Systems & Scalability, and Hardware-Aware ML.
- Focus Area 2: Applied Science Courses: Courses teaching the application of high-performance computing to specific scientific domains.
- Focus Area 3: Workshops, Labs & Modular Curriculum: Shorter-term formats like “Plug-and-Play Labs,” lecture series, or intensive workshops.
How to Apply
- Draft Your Proposal: Prepare a concise 1-2 page PDF.
- Define Milestones: Clearly state your research topic, intended publication venues, and expected timelines. Include a funding request and a basic budget.
- Open Source Commitment: Note that Google expects successful projects to be open-sourced under an Apache 2.0 or MIT license.
- Submit: Applications are reviewed on a rolling basis until June 30th, 2026.
More Detail and Submit Your Application Here
For more details on the recommended software stack or to ask specific questions, reach out to Google at tpu-rfp@google.com.
Let’s put our innovative ideas forward and secure the resources to drive the next wave of ML breakthroughs at MIKE Lab!