Atom Grants
Discover
  • Dashboard
  • Search
  • Deep Research
  • Favorites
  • Projects

    Carter Manny Award

    Limited submission

    Carter Manny Award supports emerging doctoral scholars with dissertation research and writing on architecture and its role in arts, culture, and society to advance architectural discourse.

    OverviewSimilar Grants
    OverviewSimilar Grants

    Funder: Graham Foundation for Advanced Studies in the Fine Arts

    Due Dates: November 15, 2026, at 5 p.m. Central Time (Application) | June 2027 (Decisions) | September 1, 2027 (Award begins)

    Funding Amounts: Research Award: up to $20,000 | Writing Award: up to $25,000 | One-year award period

    Summary: Supports doctoral dissertation research and writing on architecture and its role in the arts, culture, and society.

    Key Information: Departmental nomination is required, with one Research Award nominee and one Writing Award nominee permitted per department.


    Description

    Established in 1996, the Graham Foundation’s annual Carter Manny Award supports the completion of outstanding doctoral dissertations on architecture and its role in the arts, culture, and society. It recognizes emerging scholars whose work promises to challenge and reshape contemporary discourse and influence the field of architecture.

    Dissertations must focus on architecture, but may draw on architectural history, art and art history, design, engineering, landscape architecture, urbanism, and related fields. The program assists candidates in architecture, art history, fine arts, humanities, and social sciences programs working on architecture topics. Separate Research and Writing Awards support essential dissertation research and sustained work toward completion. Selection emphasizes originality, potential contributions to architectural discourse, feasibility, and the candidate’s ability to complete the dissertation.


    Atom

    See the full grant listing

    Sign in to view full eligibility details, sources, similar grants, and AI-powered analysis.