The Data Science Initiative Competitive Research Fund

Currently not accepting applications.

Award Amount: $5,000-$100,000 for one year (the Fund will support two awards of up to $100,000 each, and two to four smaller awards of up to $50,000 each.  A total of $250,000 of funding is available).
  
Eligible Applicants: Individuals who hold a faculty appointment at a Harvard school and who have principal investigator rights at that school (see Eligibility section, below).

Overview of the Data Science Initiative Competitive Research Fund

The Harvard Data Science Initiative is connecting faculty and students across all schools to advance a new science of data. By asking the right questions, driving breakthrough scientific advances, and working with data of a size and variety that was previously unimaginable, we can make startling discoveries, promote better decisions, and effect positive change.

The 2020 DSI Competitive Research Fund will support planning grants that coalesce and accelerate methodologically-focused research. For applied work, we are especially interested in projects that intersect with or are likely to have impact within or across the DSI’s research themes:

  1. Data-Driven Scientific Discovery(includes discovery of new materials, drug and gene discovery, environment, astronomy, neuroscience)
  2. Markets and Networks(includes networks and influence, innovation and crowds, digital economy, jobs, data-driven decisions, blockchain)
  3. Personalized Health(includes precision medicine, precision public health, medical informatics, diagnostics, personal devices)
  4. Evidence-Based Policy(includes equality of opportunity, healthcare economics, democracy and governance, climate change -- resilience and mitigation)

Work that is primarily methodological is also strongly encouraged. We are interested in promoting advances across many areas that relate to the science of data, including causal inference, visualization, scalable and robust inference, experimental design, interpretability and robustness, ethics (including privacy and fairness), control of false discovery, human-in-the-loop systems, reinforcement learning, adaptive data systems, deep learning, streaming algorithms, theoretical foundations, reproducibility, and data sharing.

Proposed projects should suggest the possibility of longer-term research programs and should describe creative and innovative approaches to advancing research over one to two years. If you would like to see an example of a successfully award, please contact kevin_doyle@harvard.edu.

Eligibility

This program is open to individuals who hold a faculty appointment at a Harvard school and who have principal investigator rights at that school. (Please note: Harvard Medical School faculty must hold a faculty appointment with PI rights in one of HMS’s Quad-based, preclinical departments).

Individual faculty members may only submit one application in this funding cycle. Successful applicants will be expected to give a short presentation of the funded project at a symposium during or at the end of the grant period, and to share any code that is developed through a public GitHub repository.

Application Requirements

Applications must be submitted online here by 11:30 p.m. by February 10, 2020.

Information requested in the online application includes the following:

  1. Contact information
  2. Project description that is accessible to non-specialists (limit 3 pages). The project description should include:
    1. The question or problem, and why it is important.
    2. The approach to be taken.
    3. The potential impact of the proposed work.
  3. Abridged CV or biosketch (limit two pages)
  4. List of all current or pending external sources of grant support, and information on any external funding you have applied for or intend to apply for to support the project.
  5. Budget and budget justification (limit one page). Budgets should provide enough information to convey the alignment of costs with the project. Faculty are encouraged to work with their grant administrators when including personnel and fringe benefits. We expect to make funding available in late Spring, 2020.
  6. Description of the availability of data and resources, as appropriate.

Examples of eligible expenses include:

  • Personnel, such as postdocs, research staff, graduate students, undergraduate students
  • Travel (domestic and international)
  • Acquisition of datasets

The following expenses are NOT eligible for funding:

  • Faculty salary
  • Graduate student tuition
  • Educational use
  • Subcontracts outside Harvard
  • Equipment

School assessments and/or indirect costs should not be included in your budget (the DSI will arrange these with home schools separately).

Contacts:

If you have questions about the DSI Competitive Research Fund, please email datascience@harvard.edu.