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Emerging Models and Technologies for Computation
(EMT)

CONTACTS

See program guidelines for contact information.
PROGRAM GUIDELINES

Solicitation
07-523
Please be advised that the NSF Proposal & Award Policies & Procedures Guide (PAPPG) includes
revised guidelines to implement the mentoring provisions of the America COMPETES Act (ACA)
(Pub. L. No. 110-69, Aug. 9, 2007.) As specified in the ACA, each proposal that requests
funding to support postdoctoral researchers must include a description of the mentoring
activities that will be provided for such individuals. Proposals that do not comply
with this requirement will be returned without review (see the PAPP Guide Part I:
Grant Proposal Guide Chapter II for further information about the implementation of
this new requirement).
DUE DATES

Archived
SYNOPSIS

The EMT program seeks to advance the fundamental capabilities of computer and information sciences and engineering by capitalizing on advances and insights from areas such as biological systems, quantum phenomena, nanoscale science and engineering, and other novel computing concepts. To bring fundamental changes to software, hardware and architectural design aspects of future computing models, collaborations among computer scientists, engineers, mathematicians, biologists and other disciplinary scientists are imperative.
Research of interest should move beyond evolutionary technological advances to innovations that enable fundamentally different ways of computing. These innovations should promise much higher speeds/chip densities or should solve more complex problems than traditional approaches currently permit.
The EMT program supports cross- and inter-disciplinary research and education projects that explore ideas, theory and experiments which go beyond conventional wisdom and venture into a range of uncharted territories in order to advance computing capabilities, and/or that produce innovative curricula or educational materials to help advance the training of new experts in emerging computing models and technologies. Explicit efforts will be made to support untested theories and approaches that provide plausible but high-risk opportunities. Proposals that are not clearly collaborative and/or interdisciplinary in nature are likely to be less competitive.
Abstracts of Recent Awards Made Through This Program
News
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