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.

To ensure fairness, we use a scoring rubric for consistency across reviews. We look at the criteria below to assess proposals. Proposals must comply with the required format and other Research Scholar Program guidelines.

• 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.

• Broadening Participation: Faculty is committed to broadening participation in computing through their work on a variety of initiatives, including, for example, designing and deploying programs, and training and mentoring students from historically marginalized groups.

• AI Ethics Principles: The research proposal strongly aligns with Google's AI Principles.

• November: Applications open
• December/January: Proposal reviews and scoring
• February: Committee reviews proposals, scoring and make selections
• March: Approval process for selected proposals
• April: Applicants are notified of decision

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.

To ensure fairness, we use a scoring rubric for consistency across reviews.

Faculty may apply up to a maximum of 3 times within the 7 years they received their PhD.

Faculty can receive a Research Scholar award only once. Previous Faculty Research Award recipients are still eligible to receive a Research Scholar award.

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.

The application process includes filling out an online form requesting basic information and uploading a PDF proposal via the form. As part of the online form, you will be asked to select a topic area. Please select carefully, as this will help us in ensuring your proposal is read by the appropriate reviewers. Do not send any confidential or proprietary information in your proposal. Any information you send us as part of your application will be considered not confidential regardless of any markings or designations on it.

Yes. We focus on funding social science research that looks at technology's implications and impacts on individuals and society. We typically review submissions from fields like human-computer interaction, psychology, and science and technology studies, as well as research in computer science fields with a strong emphasis on the human experience.

• The proposal should be a maximum of 5 pages if you are a sole Principal Investigator.

• The proposal should be a maximum of 7 pages if you have a co-Principal Investigator and want to include the co-Principal Investigator’s CV (a 2-page CV for a co-Principal Investigator is optional).
  
  
  • If you choose not to include the co-Principal Investigator’s CV then your proposal should only be 5 pages.
    
  • The extra 2 pages will only accommodate for an additional CV, not for additional proposal content.

• The maximum page limit includes the 2-page CV of the primary Principal Investigator, which is required for all applications (again a 2-page CV for a co-Principal Investigator is optional).

• To be fair to you and others, we do not consider proposals longer than the maximum page limit.

• We request a Google Scholar profile link as part of the online application form. Our reviewers find it helpful to be able to easily reference a Principal Investigator's publication history to see how the current proposal relates to past work the Principal Investigator has done in relevant fields. The Google Scholar profile complements, but does not replace, the Principal Investigator's 2-page CV.

• We do not require a budget breakdown since we have flat funding amounts we will grant based on region.

• We would prefer proposals to respect a minimum 10pt font size and 1-inch (2.5-cm) margins. Our reviewers value readability.

• Below is an example of what a proposal may look like (though the relative length of each section may differ by proposal).

Proposal Format

1. Overview
   1. Proposal Title
   2. Principal Investigator full name, contact information (postal address, email address, phone), affiliation (university, school, college and/or department)
      
2. Proposal Body
   
   1. Abstract
   2. Research goals, including a problem statement.
   3. Description of the work you'd like to do, as well as the expected outcomes and results.
   4. How this relates to prior work in the area (including your own, if relevant)
   5. References, where applicable.
3. Data policy
   
   1. Our goal is to support work where the output will be made available to the broader research community. To that end, we ask that you provide us with a few sentences sharing what you intend to do with the output of your project (e.g. open sourcing code, making data sets public, etc.). Please note that the awards are structured as unrestricted gifts, so there are no legal requirements once a project is selected for funding. This is simply a statement of your current intentions.
4. CV format for the principal investigators
   1. The maximum length of a Principal Investigator CV is two pages. Any submitted CV that is longer than 2 pages may be cut off at two pages before the proposal review process begins.
   2. We require a CV for at least the primary Principal Investigator on the proposal. We will accept CVs from each of the Principal Investigators listed on the proposal (up to two are allowed). Each CV must be limited to two pages.

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.

We provide support up to $60,000 USD depending on the cost of student tuition on a regional basis.

Our website is consistently updated with new programs we offer. We encourage you to connect with our Google researchers at conferences to build more opportunities for applying to research grants.

The program is designed to support one year of work. If you are selected as a recipient of a Research Scholar award, we will partner you with a Google sponsor who can navigate the potential of an extension.

Yes, the co-PI must meet the same eligibility criteria as the primary PI. We are providing an exception if the co-PI is a postdoctoral researcher.

We will be providing limited email support via [email protected]. Due to the volume of emails we receive, we may not be able to respond to questions where the answer is available on the website.

As a part of the group of engineers that review proposals for this program, we read a lot of proposals. We'd like to read more good proposals. Here's some advice on how you can improve the content of your short proposal and make reviewing it easier.

A good research grant proposal:

• Clearly specifies a problem. Good research is driven by a great problem or question, and a good proposal starts with a clearly specified one.

• Describes a specific, credible, relevant outcome. Try to identify a specific and appropriately sized outcome, to give us a clear notion of what the research award would be enabling. What will likely come to be that might otherwise not happen? While this outcome should be a decisive step towards achieving your vision, it generally won't be adequate to completely achieve it. It often helps to describe both the minimum that is likely to be accomplished and a potential best-case. Since picking the right datasets and test cases is often important, tell us which ones you plan to use.

• Crisply differentiates the proposed contribution from prior work. Please apply normal practices (citations, etc.) for documenting how your work will materially advance the state of the art. Make it clear how your work will be changing the state of the art, and not simply trying to match it.

• Tells us how the research challenge(s) will be addressed. Successful research projects combine a great problem with ideas for solutions, too. We recognize that all the answers won't be known yet, but we'd like to feel that the direction has been established, and a plausible path has been identified. (Try to avoid proposals of the form "We want to look at problem X".) It's hard to have a big impact without taking risks, but please identify what the difficulties are likely to be and how you plan to mitigate them. It may help to explain how you succeeded in addressing analogous problems in other projects.

• Puts the proposed work in context. Most projects we fund also have support from other sources. To help us understand the expected impact of Google support, please explain what funding you already have for this area of research and how the proposed work relates to your existing plans. Do you plan to build a capability for other research, provide a tool, reproduce a prior result, collaborate with others to try something out, follow up on a promising idea, or explore a new one? All are potentially of interest; we just want to know.

• Makes the case to a non-expert. 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 make at least the motivation and outcomes broadly accessible.