Research scholar program

Our team conducts research in graph mining, optimization, operations research, and market algorithms to improve Google's infrastructure, machine learning, and marketplaces. We collaborate with teams across Google and perform research in related areas, such as algorithmic foundations of machine learning, distributed optimization, economics, and data mining.

Google Health research aims to advance AI and technology to help people live healthier lives through collaborative research with public officials, clinicians, and consumers. We are developing tools to understand population health, novel algorithms to better understand and use complex medical data, and technology to help people find high-quality health information and understand their health status.

We invite proposals that will generate and understand large datasets to improve population health, develop novel algorithms for better understanding of complex medical data, and develop novel methods to extract health insights cheaper, faster, or better.

Machine learning is the foundation of Google's research, with a broad scope that includes foundational and algorithmic work, critical real-world applications, and topics, such as federated learning, information retrieval, learning theory, optimization, reinforcement learning, robotics, and recommender systems.

Our team comprises multiple research groups working on a wide range of natural language understanding and generation projects. Our researchers are focused on advancing the state of the art in natural language technologies and accelerating adoption everywhere for the benefit of the user. Natural language processing and understanding plays a major role in driving Google’s company-wide OKRs as language understanding is the key to unlocking Google’s approach: “Build a more helpful Google for everyone that increases the world’s knowledge, success, health, and happiness.”

The Quantum AI team is developing an error-corrected quantum computer and discovering valuable applications by offering a quantum computing service. We collaborate with academic partners to advance both goals, so if you have a quantum algorithm you would like to run on our service, please submit a proposal.

Research on all aspects of software development, including the engineers and the programming languages, libraries, development tools, and processes that they use.

Large language, visual, and multimodal models have made significant advances in recent years, opening up new possibilities for scientific research. We invite proposals in these four areas:

• Applications: Proposals that demonstrate how large language models can be used to advance scientific discovery in a specific field.
• Foundations: Proposals that explore broad advances in building, tuning, or deploying large models for scientific research, such as integrating language models with specialized scientific tools, developing multimodal models for understanding scientific data, and accelerating scientific analysis, experimentation, and summarization.
• Evaluation: Proposals that develop datasets or methods for benchmarking and evaluating large models for science, including evaluating domain-specific knowledge, assessing factuality and grounding, evaluating multimodal capabilities, and developing tasks that require multi-step scientific reasoning.
• HCI: Proposals that enhance scientific workflows, such as automating complex simulation pipelines, with large language models and human-in-the-loop interaction.

HCI researchers at Google design and build large-scale interactive systems that aim to be humane, simple-to-understand, and delightful to use. We work across a variety of HCI disciplines, including predictive and intelligent user interfaces, mobile and ubiquitous computing, social and collaborative computing, and interactive visualization.

Machine perception researchers at Google develop algorithms and systems to tackle a wide range of tasks, including action recognition, object recognition and detection, hand-writing recognition, audio understanding, perceptual similarity measures, and image and video compression.

Google's privacy research reaches across multiple teams, focusing on different aspects of privacy to advance the state of the art and develop tools to protect users and give them control over their data. This includes work on privacy-preserving technologies using cryptography and differential privacy, machine learning for privacy, user interface design and human-computer interactions to make communication clear and empower users, privacy policy to define Google's guiding principles for user protection, and system analysis and measurement to develop techniques to evaluate the privacy health of Google's systems.

Google's security and anti-abuse research team brings together experts from multiple disciplines to defend users from a wide range of threats. This includes work on access control, information security, networking, operating systems, language design, cryptography, fraud detection, machine learning for abuse detection, denial of service, emerging threats, user interfaces, and other human-centered aspects of security.

Google's systems and networking systems research is focused on building and deploying novel systems at unprecedented scale. Our work spans the entire spectrum of computing, from large-scale distributed systems to individual machines to accelerator technologies.

We address fundamental questions around data center architecture, cloud virtual networking, wide-area network interconnects, software-defined networking, machine learning for networking, large-scale management infrastructure, congestion control, bandwidth management, capacity planning, and designing networks to meet traffic demands.

Applications are open to academic researchers who are currently advising students and conducting research in technology and computing at institutions. Applicants must be a full-time assistant, associate, or professor at a university or degree-granting research institution and have received their PhD within seven years at the time of the application submission.

Institutions:

• We accept applications from full-time faculty at universities around the world. Funding is focused on supporting the faculty’s research. We do not allow applications from non-degree-granting research institutions.
• Since our funding is structured as unrestricted gifts to degree-granting Universities, we cannot process awards to other institutions (e.g. not-for-profits institutions, hospitals, non-degree-granting research institutes, etc) even if they are affiliated with a University. A Principal Investigator must apply in his or her capacity as a university professor and must be able to accept an award through that University.

Principal Investigator Requirements:

• Global faculty who have received their PhD less than 7 years from submission from degree-granting institutions who are doing research within fields relevant to Google.
• An applicant may only serve as Principal Investigator or co-Principal Investigator on one proposal per round, they cannot be listed on two separate proposals.
• We understand that titles may differ globally. In order for someone without the title of professor to apply, he or she must be a full-time faculty member at an eligible institution and serve as a formal advisor to masters or PhD students. We may, at our discretion, provide funding for Principal Investigators who advise undergraduate students at colleges that do not award advanced degrees.

Past Applicants:

• If an applicant’s proposal was not selected for funding the previous round, they are welcome to apply with a new proposal (or substantively revised proposal) the following round. A Principal Investigator can apply a maximum of 3 times within the 7 years post-PhD.

Filename:

Submit your proposal and CV as a single PDF file. Name the file in the following format: "[First InitialLast name]-2025" (e.g., "JDoe-2025"). Use only letters, numbers, and hyphens.

Proposal Length:

• 5 pages maximum for a single Principal Investigator (PI) submission
• 7 pages maximum for submissions with a co-PI with CV

Formatting:

• Single-spaced
• 1-inch margins
• Times New Roman 12-point font

Proposal should include the following numbered sections:

Overview (3 pages max):

1. Proposal Title
2. Full name, contact information (postal address, email address, phone), and affiliation (institution and/or department) of PI(s)
3. Abstract (concise summary of proposal)
4. Research goals and problem statement
5. Description of the proposed work, expected outcomes, and results
6. Discussion of how the research relates to prior work (including your own)
7. Explanation of your qualifications to conduct this research
8. For ongoing projects, explain how this funding (whether by unrestricted gift or another type, specified in the RFP) would enhance your existing project.
9. Data policy: Describe your intentions for sharing the project's output with the broader research community (e.g., open-sourcing code, making datasets public). Please note that for those awards that are structured as unrestricted gifts, there are no legal requirements once a project is selected for funding. This is simply a statement of your current intentions. However, for research area topics that are not awarded as unrestricted gifts (usually those that require the use of a specific product, methodology, or other constraint), open sourcing the software, models, or other intellectual property developed during the project will be a mandatory condition for receiving the award, unless otherwise specified in a separate agreement between Google and the recipient.

CVs (4 pages max):

1. Primary PI: 2-page max CV required
2. Co-PI: 2-page max CV (optional)

Important notes

1. The co-PI's CV is the only content allowed on the additional 2 pages of a co-PI proposal. Any submitted CV longer than 2 pages will be truncated before review.
2. Proposals without a co-PI's CV should not exceed 5 pages.
3. References should be excluded from the proposal itself. Instead, use the designated sections in the application form for this information.

Please do not include budget details in your proposal. We will be providing flat funding amounts based on the cost of student tuition on a regional basis.

Co-PIs must generally meet the same eligibility criteria as primary PIs, except in cases where the co-PI is a postdoctoral researcher.

While we are likely to fund submissions that align with the listed research areas and subtopics, we are open to innovative proposals within these areas.

Here's how to strengthen your proposal:

1. Clearly define the problem. Good research starts with a compelling question.
2. Describe a specific, achievable outcome. What will this research enable that wouldn't happen otherwise, and how? Outline both minimum expected and best-case scenarios, specifying the datasets and test cases you'll use.
3. Differentiate your contribution. Clearly explain how your work advances the state of the art, using citations and other standard practices.
4. Outline your approach. Explain your plan for addressing the research challenges, even if all answers aren't yet known. Identify potential risks and mitigation strategies.
5. Contextualize the work. Describe existing funding and how this proposal fits into your broader research goals. How will this research be used? Will it build research capability, create a tool, reproduce a result, foster collaboration, follow up on an idea, or explore a new one? We are interested in all possibilities.
6. Make it accessible to non-experts. While we try to have your proposal reviewed by a Google expert in your field, it will also be read by non-experts, so please ensure the motivation and outcomes are understandable to a broad audience.

Your proposal should ultimately demonstrate how your research aligns with our mission to recognize and support academic researchers whose work in computing and technology makes a positive difference in the world.

We completely understand the desire to receive feedback and do our best to meet this request. However, due to the high volume of applications received, you may not receive feedback on your proposal.

December/January: Applications open

February-May: Proposals are under review

June: Applicants are notified of decision

Only complete applications that meet the following criteria will be scored:

• Submitted by eligible applicants
• Related to computing or technology
• Adhere to the required formatting guidelines

Scoring will be based on the following areas:

• Faculty merit: Faculty is accomplished in research, community engagement, and open source contributions, with potential to contribute to responsible innovation.
• Research merit: Faculty's proposed research is aligned with Google Research interests, innovative, and likely to have a significant impact on the field.
• Proposal quality: The research proposal is clear, focused, and well-organized, and it demonstrates the team's ability to successfully execute the research and achieve a significant impact.
• AI Ethics principles: The research proposal strongly aligns with Google's AI Principles
• For research area topics that require the use of a specific product, methodology, or other constraint, we will evaluate your project based on how well it adheres to and utilizes these aforementioned factors, as well as the overall quality of your approach.

Funding awards made in any form should not be used for overhead or indirect costs.

Faculty members are eligible to receive the Research Scholar award only once.

Please reach out to research-awards@google.com with any questions or concerns, and our team will be happy to assist you.