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Computational Modeling & Technical Feasibility Analysis

Active
Federal

Contract Overview

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

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This subcontract for Computational Modeling and Technical Feasibility Analysis supports prime contractors on DARPA SHINE projects within the Department of Defense. The scope of work involves performing theoretical analyses and computational modeling of neural circuits, utilizing first-order engineering calculations to provide quantitative justification for selectivity. The project requires specialized expertise in mathematical biology and high-performance computing to deliver computational models, feasibility reports, and quantitative data. The opportunity was posted on September 3, 2026, with a response deadline of October 9, 2026, under NAICS code 541690.

General Info

Subcontract for DARPA SHINE computational modeling and technical feasibility analysis for neural circuits.

Agency

Department Of Defense → Defense Advanced Research Projects AgcyView Agency

NAICS

541690 - Other Scientific and Technical Consulting ServicesView NAICS

Place of Performance

VA

Set-Aside

NONE

Documents

This scope was carved out of DARPA-PA-25-07-06.

The full solicitation package (5 documents), including the RFP, is on the prime solicitation, not on this scope.

View the prime solicitation

Selective Harnessing of Intrinsic Neuroplasticity Engineering (SHINE)

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Timeline

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Organization & Contact Information

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AgencyDepartment Of Defense → Defense Advanced Research Projects Agcy
ContactsNo contacts available
OfficeN/A
Organization / Agency
Department Of Defense → Defense Advanced Research Projects Agcy
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Office AddressN/A
ContactsNo contact information available

Full Description

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Performs theoretical analyses and computational modeling for prime contractors on DARPA SHINE projects. Conducts first-order engineering calculations and theoretical modeling of neural circuits to provide quantitative justification of selectivity. Requires high-performance computing and mathematical biology expertise. Delivers computational models, feasibility reports, and quantitative data.

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