Data Science Grants @ Brown

The current grant cycle is closed; we will update this page when we plan to accept new proposals. 

Please read criteria carefully. (See previously funded projects; please note, our criteria have changed.)

Brown's Data Science Initiative offers funding opportunities for collaborative projects that support our mission, namely to:

  • facilitate and conduct both domain-driven and fundamental research in data science;
  • increase data fluency and educate the next generation of data scientists; 
  • explore the impact of the data revolution on culture, society, and social justice.

We are particularly interested in funding new initiatives and collaborations, and will not fund the continuation of existing research projects. If you would like to find out more, please contact us at [email protected]. For 2019-2020, DSI will be offering 2 types of grants (funding amounts are approximate):

Seed Grants (<$15,000)

We are accepting proposals for smaller grants for early-stage or exploratory projects, and welcome proposals to fund undergraduate research involvement. Proposals are subject to eligibility and criteria described below.

Collaborative Grants (>$50,000)

To increase significant data science research on Brown’s campus, DSI also seeks proposals for larger grants that involve collaboration among domain researchers and data science faculty. Proposed projects must be new or in some way additive, rather than a continuation of existing research. We will prioritize projects that cross disciplinary boundaries and are designed to lead to larger-scale external funding in data science or in data-intensive domain disciplines.  



Brown faculty and postdoctoral researchers are eligible to apply. We also welcome applications from undergraduate and graduate students if submitted through a faculty sponsor. We plan to fund both small and larger grant proposals. Please note that we do not provide funding for faculty salaries. We anticipate having $200 – $250k available in FY20.


Successful proposals should address at least one of these criteria:

  • The proposed project initiates a new interdisciplinary research direction or catalyzes new collaborations across disciplines or units, potentially leading to a competitive external grant proposal.
  • The project advance Brown’s educational goals in data science.
  • The project explores the impact of the data revolution on culture, society, and social justice.


Proposals should be 1-5 pages long and address the following:

  • Context and background
  • Project summary
  • How does your proposal address our criteria? What is new and why should we fund you?
  • For Collaborative Grants, describe the cross-disciplinary nature of the project and your plans for pursuing external funding.
  • What are your measures of success?
  • Timeline and budget (including budget justification)

Please write your proposal with a broad audience of researchers in mind. We encourage applicants to list a few potential reviewers (at Brown) in their proposal. Please submit proposals to [email protected].

Review process

Please submit proposals by December 1. We will notify applicants by mid-January. Proposals will be reviewed by a DSI committee (potentially plus other Brown ad hoc reviewers). We will evaluate the criteria mentioned above, the anticipated risks and rewards of the proposed project, and the budget in the decision process.

Successful applicants will be expected to

  • provide a brief description with an image for the DSI website;
  • work with a DSI liaison to keep track of progress (for large projects only);
  • attend a 2 hour annual gathering of grant recipients (and give a short talk or poster presentation);
  • provide a written 1-2 page final report of findings and outcomes.

Examples of funded activities

Projects that we would be interested in funding include, but are certainly not limited to:

  • Working lunches/discussion groups to bring together colleagues from different units or disciplines to work on a competitive grant proposal or develop new research directions
  • Preliminary data collection and analysis for preparing an external funding proposal
  • Purchase of data from Twitter or subscription-based data providers, for instance to facilitate an undergraduate research project or course
  • Graduate student or postdoc funding, for initiating a new interdisciplinary data science research project
  • Course development of co-taught courses at the interface between data science and the humanities
  • Data science bootcamps for undergraduate or graduate students in the humanities, life, or social sciences
  • Bringing in high-profile visitors for lectures or collaboration