Defense Advanced Research Projects AgencyWork With UsOpportunities

Opportunities

Established in 1958 as part of the U.S. Department of Defense, DARPA pursues opportunities for transformational change rather than incremental advances. It does so collaboratively as part of a robust innovation ecosystem that includes academic, corporate, and governmental partners. To fulfill its mission, the Agency relies on diverse performers from throughout this ecosystem to apply multi-disciplinary approaches to both advance knowledge through basic research and create innovative technologies that address current and predicted practical problems through applied research. The list of selected opportunities displayed below is provided for convenience. For a complete listing of DARPA opportunities please visit the FedBizOpps website. More

In addition to program-specific opportunities, each DARPA technical office maintains an “office-wide” Broad Agency Announcement (BAA) that covers a range of technical areas of interest to each particular office. The office-wide BAAs are refreshed on an annual basis and offer a mechanism for researchers to reach DARPA with ideas that they feel could be valuable to national security.

 

10/4/2017
Microsystems Technology Office Commercial Performer Program Announcement
MTO
The Defense Advanced Research Projects Agency (DARPA) Microsystems Technology Office (MTO) is seeking to support innovative ideas relevant both to the commercial sector and to Department of Defense (DoD) applications.
9/13/2018
Microsystems Technology Office Office-wide Broad Agency Announcement
MTO
This announcement seeks revolutionary research ideas for topics not being addressed by ongoing MTO programs or other published solicitations.
6/30/2017
Lifelong Learning Machines (L2M)
MTO
DARPA is soliciting highly innovative research proposals for the development of fundamentally new machine learning approaches that enable systems to learn continually as they operate and apply previous knowledge to novel situations. Current artificial intelligence (AI) systems only compute with what they have been programmed or trained for in advance; they have no ability to learn from data input during execution time, and cannot adapt on-line to changes they encounter in real environments.