Application Deadline: December 1, 2022.
The Research Scholar Program aims to support early-career professors who are pursuing research in fields relevant to Google. The Research Scholar Program provides unrestricted gifts to support research at institutions around the world, and is focused on funding world-class research conducted by early-career professors.
Google encourage submissions from professors globally who are teaching at universities and meet the eligibility requirements. It is Google’s hope that this program will help develop collaborations with new professors and encourage the formation of long-term relationships.
Awards are disbursed as unrestricted gifts to the university and are not intended for overhead or indirect costs. They are intended for use during the academic year in which the award is provided to support the professor’s research efforts.
- Applicants must be a full-time assistant, associate, or professor at a university or degree-granting research institution at the time of the application submission.
- Post doctoral staff can only serve as a co-PI, not a primary PI.
- Applicants must have received their PhD within seven years of submission (e.g. applicant in 2022 must have received PhD in 2015 or later).
- We consider exceptions for applicants who have been teaching seven years or fewer and had delays, such as working in industry, parental leave, leave of absence, etc. This exception request can be documented on the application.
- Applicants can submit one application per round.
- Faculty can only serve as a PI or Co-PI per round. Applicants cannot serve on two separate proposals.
- Applicants can apply a maximum of 3 times within the 7 years post-PhD.
The funds granted will be up to $60,000 USD and are intended to support the advancement of the professor’s research.
Google ask applicants to categorize their proposals into one of the following areas of interest to Google in Computer Science and related fields:
- Algorithms and optimization
- Applied science
- Health research
- Human-computer interaction
- Machine learning and data mining
- Machine perception
- Natural language processing
- Quantum computing
- Software engineering and programming languages
- Structured data, extraction, semantic graph, and database management
- Systems (hardware and software)
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