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This Pre-Solicitation opportunity from Department Of Transportation was posted on July 23, 2026. The submission period has ended. Browse the details below for market research, or find similar active opportunities.

Exploratory Advanced Research (EAR) Program FY 2026 Data Science Solicitation

Closed
693JJ3-26-BAA-0006Federal

Contract Overview

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

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NAICS: 541715
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NAICS: 541715
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AI Contract Overview

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The Exploratory Advanced Research (EAR) Program FY 2026 Data Science Solicitation, identified by solicitation number 693JJ3-26-BAA-0006, is a presolicitation notice issued by the Federal Highway Administration under the U.S. Department of Transportation to advance high-risk, transformational research in data science applications for highway transportation systems. The program seeks to engage and expand the community of researchers applying emerging and advanced data analytic methods to address long-term challenges in transportation planning, infrastructure renewal, safety, congestion reduction, and environmental sustainability. Objectives include demonstrating the potential of exploratory data techniques to deliver significant improvements in system performance and fostering innovation through federal investment in novel scientific approaches. The solicitation is open to all eligible entities with no set-aside for small businesses or socioeconomic categories, and proposals must be submitted electronically by the deadline of August 7, 2026, via the SAM.gov platform. The contracting office is located in Washington, DC, with primary point of contact Tamiko Aikens. While the full solicitation document detailing evaluation factors, proposal structure, deliverables, and contractual requirements is not yet available, the program is structured as a Broad Agency Announcement (BAA), indicating flexibility in award methods and a focus on research quality and innovation over cost-based selection. No specific contract value, pricing details, delivery schedules, FOB terms, or packaging requirements are outlined in this presolicitation, as these will be defined in the formal solicitation to be released in mid-August 2026. The place of performance is identified as Washington, DC, and all administrative details including payment, invoicing, and contracting officer information will be established upon award.

General Info

FY 2026 BAA for high-risk data science research in highway transportation, due August 7, 2026, via SAM.gov.

NAICS

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

Place of Performance

DC, USA

Set-Aside

NONE

Documents

1

Pre-solicitation Notice for BAA 693JJ3-26-BAA-0006 EAR Program FY 2026 Data Science

PDF, Low prioritypresolicitation
Low

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Timeline

PhaseClosed
Posted

Presolicitation

Response Deadline

Deadline has passed

Submission Closed

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Organization & Contact Information

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AgencyDepartment Of Transportation → 693JJ3 Acquisition And Grants Mgt
Contacts1 person available
OfficeWASHINGTON, DC, 20590, USA
Office AddressWASHINGTON, DC, 20590, USA
Contacts
Tamiko Aikens

Full Description

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DESCRIPTION OF PROGRAM: The EAR Program addresses the need to conduct research on
longer term and higher risk breakthrough topics with the potential for transformational
improvements to plan, build, renew, and operate safe, congestion free, and environmentally sound
transportation systems. The Program scans broadly for advances in science and engineering to
identify research topics where FHWA investment has the potential to make a significant impact.
The EAR Program has identified an Agency need for data science for highway transportation
research with the following objectives:



1. Engage and expand the community of researchers interested in applying emerging and
advanced data methods for highway transportation research.
2. Demonstrate potential of emerging and exploratory data analytic techniques for highway
transportation.


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