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DARPA's Biological Technologies Office (BTO) Office-Wide Broad Agency Announcement (HR001126S003) seeks abstracts and proposals that leverage biological properties and processes to revolutionize the ability to protect warfighters, with an explicit emphasis on applying artificial intelligence and machine learning across biological science.
Priority research areas include machine learning and AI applications, combat casualty care, human performance optimization, materials/sensors/processing, agricultural and environmental solutions, security and surveillance, and biomedical and biodefense initiatives. Abstracts are accepted on a rolling basis until September 30, 2026.
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Or search similar grants →According to the current listing, eligibility includes: Open to industry, universities, and other research organizations. Specific eligibility, cost-sharing, and U.S.-person requirements are detailed in the full BAA. Confirm the full requirements in the official notice before applying.
Applications for DARPA Biological Technologies Office (BTO) Office-Wide Broad Agency Announcement HR001126S003 for AI and Machine Learning in Biological Technologies are due September 30, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
DARPA Biological Technologies Office (BTO) Office-Wide Broad Agency Announcement HR001126S003 for AI and Machine Learning in Biological Technologies is funded by Defense Advanced Research Projects Agency (DARPA), Biological Technologies Office (BTO). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Biological Technologies is sponsored by Defense Advanced Research Projects Agency (DARPA), Biological Technologies Office (BTO). Supports revolutionary research leveraging biological properties/processes to advance national security and protect warfighters; excludes incremental improvements. Key focus areas include advanced machine learning and AI for biological data and systems, combat casualty care, human performance optimization, bio-inspired materials, sensors, manufacturing, agricultural, ecological, and environmental security, biosafety, biosecurity, next-generation surveillance, and biomedical and biodefense technologies. Foreign companies may be eligible as DARPA aims for international collaboration for national security.
DARPA's Biological Technologies Office (BTO) office-wide Broad Agency Announcement (BAA HR001126S0003) funds research that leverages artificial intelligence and machine learning to advance the biological sciences for national security. Priority interest areas include warfighter health, biodefense, diagnostic systems for chemical and biological threat detection, medical countermeasures, materials and sensors, agricultural and environmental applications, security and surveillance, and novel approaches to tactical care and performance recovery. Abstracts are accepted on a rolling basis through September 30, 2026, with award sizes varying by the scope of the proposed effort.
The NSF Computer and Information Science and Engineering: Future Computing Research (Future CoRe) program (NSF 25-543) supports foundational computing research and education with a strong emphasis on AI and machine learning. The program funds research that advances the foundations of computing including AI/ML theory, algorithms, systems, and applications. Future CoRe supports small to medium-sized research projects that can have significant impact on computing foundations. The program has target dates of February 5, 2026 and September 10, 2026 for proposal submissions (note: these are target dates, not deadlines, meaning proposals may be submitted at any time but will be reviewed in batches around these dates). Investigators may not serve as PI, co-PI, or Senior/Key Personnel on more than two proposals submitted within any consecutive 12-month period across all Future CoRe programs. This is one of NSF's primary mechanisms for funding fundamental AI and machine learning research at U.S. academic institutions, covering areas such as machine learning theory, natural language processing, computer vision, robotics foundations, and human-AI interaction.
The Department of Energy's Office of Technology Commercialization has opened the FY26 Genesis Mission SBIR/STTR Phase I opportunity, funding small business research across four AI-for-science topic areas tied to DOE's Genesis Mission. Scaling the Biotechnology Revolution seeks advanced AI applications for biochemicals and bioproducts, including AI tools to support biomolecular design and to accelerate bioreactor design and biomanufacturing. Realizing Quantum Systems for Discovery covers AI for quantum computing and networking, specifically qubit decoherence mitigation, quantum error correction, and automating and optimising quantum resource estimation tools. Designing Materials with Predictable Functionality seeks AI frameworks enabling inverse design, where materials are engineered backwards from specific required properties, for energy and manufacturing applications. Achieving AI-Driven Autonomous Laboratories covers integration of AI into experimental workflows using advanced robotics, AI for network operations, diagnostics and remote handling. Phase I awards are up to 250,000 dollars over six to 12 months, with approximately 40 awards totalling 10 million dollars and lifecycle funding up to 44 million dollars. The defining feature of this cycle is a mandatory pitch-first process: companies submit a 700-word pitch answering four equally weighted questions covering summary, technical promise, commercialisation potential and team qualifications, and only accepted pitches are invited to submit a full application. Pitches were due 10 September 2026 at 2:00pm ET. A company may submit a maximum of three pitches.
The ONR Long Range Broad Agency Announcement (N00014-25-S-B001) is the Office of Naval Research's primary mechanism for soliciting research proposals across all naval science and technology priority areas. The BAA accepts proposals on a rolling basis through September 30, 2026 and covers ONR's full spectrum of research interests with particular emphasis on AI-related topics including autonomous maritime systems, human-machine teaming, machine learning for sensor fusion, cooperative autonomous swarm technology, undersea autonomy, and AI-enabled decision superiority. Proposals can be funded through multiple mechanisms including individual investigator grants, the Young Investigator Program (~$510K over 3 years for early-career faculty), and Multidisciplinary University Research Initiative (MURI) awards ($1.5M/year for 3-5 years for research teams). ONR recommends contacting relevant program officers before submitting to discuss alignment with current research priorities. The BAA supports basic research (6.1), applied research (6.2), and advanced technology development (6.3) across the full range of naval-relevant science and engineering disciplines.
On June 3, 2026, four DARPA Biological Technologies Office SBIR topics close simultaneously — SWiFT, BARK, EXPOSITION, and Medical Swarm Robotics. Combined Phase I plus Phase II potential exceeds $6 million per company, and together they sketch a coherent strategy of distributed, autonomous, dual-species combat casualty care that depends on small businesses, not primes, to actually build.
Read articleDARPA pre-released Release 6 of its FY26 SBIR BAA on September 2, 2026. Five of the seven SBIR topics belong to the Biological Technologies Office, and four of those describe one continuous problem: keeping a casualty alive with no surgeon, no imaging, and no evacuation. Here are the award sizes, the Direct-to-Phase-II gates, and the sequencing DARPA is buying.
Read articleDARPA BTO pre-released four FY26 SBIR/STTR topics on April 30, 2026, with proposals due June 3. Two topics — SWiFT and EXPOSITION — offer Direct-to-Phase-II awards up to $1.5M, bypassing the standard Phase I gate. Here is what each topic is actually solving, why the DP2 structure matters, and how small biotech, surgical robotics, and battlefield-medicine teams should decide whether to compete.
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