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DEEP TRANSFER LEARNING BASED COGNITION ENGINE FOR NETWORK-ADAPTIVE WAVEFORM DESIGN

Active

Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

AI Contract Overview

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This contract involves a project titled Deep Transfer Learning Based Cognition Engine for Network-Adaptive Waveform Design, currently held by the San Diego State University Foundation. The current award, identified as FA875023C0521, is valued at 350,000 dollars and is structured as a cost-no-fee agreement. The work is managed by the Department of Defense through the AFRL RIK office located in Rome, New York. The contract is projected to end on November 5, 2026, and is identified as a high-confidence full-recompete opportunity. The upcoming solicitation is expected to be available via full and open competition. The project falls under NAICS code 541715, and Steven M. Appler serves as the primary point of contact for the agency.

General Info

SDSU Foundation $350,000 DoD contract for waveform design ending November 5, 2026.

Agency

Department Of Defense → FA8750 Afrl Rik

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)

Place of Performance

NY, 921821901, USA

Set-Aside

NONE

Documents

0

No documents available

Documents will appear here when they are available.

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Timeline

PostedMay 5

pre-forecast

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Organization & Contact Information

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AgencyDepartment Of Defense → FA8750 Afrl Rik

Contacts1 person available

OfficeROME, NY, 13441-4514, USA

Organization / AgencyDepartment Of Defense → FA8750 Afrl Rik

Office AddressROME, NY, 13441-4514, USA

Contacts

Steven M. Appler

contact@example.gov

+1 (555) 000-0000

Full Description

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Predicted recompete opportunity based on federal award data.
Current Contract: FA875023C0521 Incumbent: SAN DIEGO STATE UNIVERSITY FOUNDATION Contract Value: $350,000 Potential End Date: 2026-11-05T00:00:00.000Z Competition: FULL AND OPEN COMPETITION Pricing: COST NO FEE Classification: full-recompete (Confidence: high - 90/100)

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