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Theoretical/Applied Research Scientist

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 a Theoretical/Applied Research Scientist supports the Defense Advanced Research Projects Agency within the Department of Defense. The role focuses on conducting high-risk, high-reward research to secure fundamental scientific breakthroughs for prime contractors. Key responsibilities include investigating innovative approaches to drive revolutionary advances through the use of specialized simulation software and high-performance computing. The contractor is required to deliver theoretical models, validated experimental data, and scientific papers while maintaining compliance with NIST SP 800-171 standards for the protection of controlled unclassified information. This opportunity falls under NAICS code 541713 and has a response deadline of June 1, 2027.

General Info

Research Scientist subcontract for DARPA focusing on high-risk research, due June 1, 2027.

NAICS

541713 - Research and Development in Nanotechnology

Place of Performance

VA

Set-Aside

NONE

Documents

This scope was carved out of DARPA-PA-26-08.

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

View the prime solicitation

DARPA Research Solutions Opening

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Organization & Contact Information

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

Full Description

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Performs high-risk, high-reward research to achieve fundamental scientific breakthroughs for prime contractors on DARPA projects. Investigates innovative approaches to enable revolutionary advances using high-performance computing (HPC) and specialized simulation software. Complies with NIST SP 800-171 for CUI protection where applicable. Delivers scientific papers, theoretical models, and validated experimental data.

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