The Michigan Institute for Data Science (MIDAS) is pleased to announce the next round of pilot funding. MIDAS will fund research in any area of data science and artificial intelligence (AI), including the theoretical foundations, methodology and tools, the innovative application of the methodologies in any research area, and their implications for society and the public interest. We are particularly interested in funding pioneering work that promises high reward, major impact, promotion of public interest, and potential for major expansion.
All complete submissions will be considered; however, we encourage proposals that fit with at least one of the three priorities:
- Enabling major external grants. A major external grant application, submitted within one year of receiving PODS funding, should be one of the main deliverables for projects in this priority area. The research team can use this pilot grant to obtain preliminary data, test a prototype, or fill other gaps to strengthen the external grant application. In the transition plan (see “How to Apply”), applicants should identify the specific target grant opportunity and the application timeline. Applicants are welcome to discuss with MIDAS how we can support your external proposal regardless of whether you receive our pilot funding.
- The transformative use of data science and AI methodology in any application domain. Expectations for such proposals will depend on the current state-of-the-art usage of methodologies in each domain. The focus is less on the sophistication of the methodology, but more on its impact in a specific domain. Proposals in this priority area are expected to be collaborations between data science / AI methodologists and domain scientists. Applicants are welcome to discuss with MIDAS before submitting the full proposal if they would like MIDAS to help identify interdisciplinary collaborators.
- Improving the reproducibility of data science and AI research and the practices of the U-M community. Proposals fit this priority area if: (A) In addition to fitting with one of the two priorities above, they pay special attention to the reproducibility of their results; or (B) They will generate insights or practical methods that can improve the reproducibility of research at U-M. Applicants are welcome to discuss with MIDAS before submitting the full proposal about how to use existing MIDAS programs to build synergy and for dissemination of best practices.
Award Information: 10-12 projects will be awarded for a duration of 12-18 months, based on a competitive process. Two models of funding are available: 1) $10K-30K, MIDAS will provide 100% of the funding, with no cost-share required. 2) $30K-$70K, with cost-share above the first $30K in a ratio of 1:1. For example, if you request $70K, your cost-share portion will be $20K and MIDAS will provide $30K base + $20K cost-share match = $50K. The project team is responsible for securing cost-share from individual research accounts or unit contributions. Please email email@example.com for questions regarding the cost-share.
Who May Apply: Principal Investigators (PIs) and co-PIs should be U-M (Ann Arbor, Dearborn, Flint) researchers who are eligible to apply for federal grants, and should not have been a PI or co-PI of a MIDAS grant awarded on or after May 2019. An individual may participate as PI/co-PI on only one proposal. Co-investigators, consultants and other personnel are not limited by this restriction. All PIs and co-PIs should be MIDAS affiliate members.
- 11:59 pm, March 19, 2021: Letters of intent due
- 11:59 pm, April 16, 2021: Full proposals due
- May 28, 2021: Awards announced
- By June 10, 2021: Projects start
How to Apply:
Letters of intent should be submitted through Infoready. Letters of intent are for planning purposes only, and will be approved to submit full proposals, provided the submitters are eligible. The letter should be one .pdf file containing the following:
- The tentative title of the proposal.
- The names and affiliations of the PI and co-PIs (co-PIs may change in the full proposal).
- An abstract (up to 300 words), which may also include how the proposal may fit one (or more) of the three priority areas, and how the team plans to collaborate with MIDAS.
The full proposal should be one .pdf file submitted through Infoready, containing the following components. Incomplete applications will not be reviewed.
- Project description, up to 6 pages, with the font size of 10 or above. This should include Specific Aims, background, significance and innovation, and methods. If applicable, it should also address how it fits one or more of the three priority areas. In addition, research teams are welcome to describe how they will collaborate with MIDAS, if applicable, to take advantage of existing MIDAS programs for their projects and to benefit the U-M data science community, such as through research workshops and resource development.
- A transition plan (up to ½ page) that describes the strategy for follow-on funding and activities, such as external grants, continuing research plan, data products and/or commercialization.
- A Statement of Societal Impact (up to ½ page) that describes how this project will benefit the society, and, if any, potential negative impact that needs to be carefully avoided.
- References (no page limit).
- Biosketch in NSF or NIH format for all senior personnel. In addition, all U-M internal grant awards received since 2016 should be listed (this can be on an additional page).
- A detailed budget and budget justification. You may use our template or any other template of your choice.
- Proof of cost-share (such as a letter from the department chair or a statement about the PI’s research account).
- If an IRB is required for the project, include a description of the status of the IRB application.
- Innovative concept and/or approach;
- The significance of the research questions;
- The fit with at least one of the priority areas;
- Likelihood of success;
- Impact to the research field;
- Potential for continuation, external funding and/or commercialization.
- All teams will be expected to present at MIDAS events and participate in MIDAS activities for data science research, training and community building.
- All publications, public presentations and products from this award should acknowledge MIDAS.
For questions, please contact: firstname.lastname@example.org