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ERI Funding Opportunities

Welcome to the ERI Funding Opportunities Site

College of Engineering campus
Research drives excellence in the College of Engineering by serving as a magnet to attract and retain outstanding faculty and students. Funding opportunities relevant to the College of Engineering will be posted here. If you are interested in pursuing any of these opportunities please contact ERI at eri-pre@iastate.edu for assistance or additional information. New opportunities are posted weekly. To have the new opportunities delivered directly to your inbox please subscribe using your ISU email address. One email per week.

Joint Additive Qualification for SustainmentSupplier Qualification

America Makes

Solicitation: JAQS-SQ

Posted Date: August 6, 2025

Proposal Due Date: October 2, 2025

America Makes and the National Center for Defense Manufacturing and Machining (NCDMM) are proud to announce a new open project call funded by the Office of the Under Secretary of Defense, Manufacturing Technology Office (OSD ManTech), worth a total of $1.7M. The project call, Joint Additive Qualification for Sustainment – Supplier Qualification (JAQS-SQ) – Group 1​, aims to accelerate the integration of non-traditional suppliers and scale Defense Industrial Base capabilities by training and supporting additive manufacturers to meet required process control documents (PCDs) for qualified additive manufacturing (AM) production.

 

Mapping Machine Learning to Physics (ML2) Proposers Day

DARPA

Solicitation: DARPA-SN-25-102

https://sam.gov/workspace/contract/opp/aaba444f0eb8450a8ad430a28c595d36/view

Posted Date: August 12, 2025

Event Date: August 26, 2025, from 9:00 AM to 3:00 PM Eastern Time (ET)

PROPOSERS DAY
DARPA I2O is sponsoring an unclassified hybrid Proposers Day in support of the anticipated Mapping Machine Learning to Physics (ML2P) Program Solicitation (PS). The purpose of this event is to provide information on the ML2P technical goals and challenges, address questions from potential proposers, and provide an opportunity for potential proposers to consider how their research may align with the ML2P program objectives. Attendance is voluntary and is not required to propose to the ML2P PS.

 

Endless Generative Waveforms (End-Gen)

DOI

Solicitation: DOIDFBO250065

https://sam.gov/workspace/contract/opp/2ee81e73f329420c8f76aabf05ff2106/view

Posted Date: August 12, 2025

Proposal Due Date: September 29, 2025

This notice constitutes the official issuance of Broad Agency Announcement (BAA) DOI-BAA-ENDGEN-FY25-02, and sets forth research for Endless Generative Waveforms (End-Gen)

ENDGEN Program Summary: End-Gen proposes a program seeking to develop novel methods of arbitrary generative waveforms, enabling the intelligence community, and wider USG, to more easily and cheaply create wireless information exchange protocols without costly, delayed human development cycles. This will be accomplished across two developmental technical areas (TA):

TA-1 In Situ Discovery: End-Gen generative frameworks, loaded onto smart radios are placed within the desired environment, given human mission objectives, and generate waveforms through an adaptive training method.

TA-2 Ex Situ Conservation: End-Gen foundational generative frameworks, prompted to create waveforms suitable for the desired environment and human objectives, create outputs which are placed onto smart radios.

Offerors are required to submit a proposal that addresses all three phases of the program for one of the TAs per proposal.

Mapping Machine Learning to Physics (ML2P)

DARPA

Solicitation: DARPA-SN-25-101

https://sam.gov/workspace/contract/opp/c6233393d88d450ebf942f87430516fe/view

Posted Date: August 08, 2025

Notice of intent only

The purpose of this Special Notice is to provide public notification of additional research areas of interest to the Defense Advanced Research Projects Agency (DARPA) Information Innovation Office (I2O), specifically for the forthcoming Mapping Machine Learning to Physics (ML2P) program by I2O Program Manager, Bernard McShea. If released, the solicitation will be made available at https://sam.gov.

PROGRAM BACKGROUND AND OBJECTIVES

We stand at a pivotal moment in the evolution of technology. Machine Learning (ML) is transforming industries at an unprecedented pace, powering everything from personalized healthcare to autonomous systems. But as these models grow in scale and complexity, so does their hunger for energy. The challenge? Our planet’s electrical resources are limited and demand quickly outpaces supply. To sustain innovation without compromising the future of our environment and energy resources, we need a new paradigm: a more innovative, sustainable approach to ML.

The Department of Defense (DoD) faces the challenge of ML at the edge, in a resource-constrained battlefield, placing an even greater requirement on the efficiency of electrical usage. The requirement of energy-aware ML is in addition to the standing need to extend warfighters’ existing hardware capability (e.g., increased security, range, and durability). Energy-aware ML is optimized for efficiency with respect to power (i.e., Joules (J)) for the lifespan of the ML, from dataset selection to model inference, while retaining model performance. For example, aerial, surface, and submersible Unmanned Autonomous Systems (UASs) have a limited battery capacity that must serve all mission needs, including on-system (e.g., propulsion, communication, processing) and pre-mission planning and retraining requirements.

Development of an Automated Driving System (ADS) National Strategy for the National Park Service (NPS) Through the Use of Pilots in an Operational Setting

DOT

Solicitation: 693JJ3-25-BAA-0004

https://sam.gov/workspace/contract/opp/5824887632c44af49ed61a3e22b15881/view

Posted Date: August 08, 2025

White Paper no later than August 22, 2025.

Proposal Due Date: October 03, 2025

The Federal Highway Administration’s (FHWA) Office of Federal Lands Highway (FLH), in partnership with the National Park Service (NPS), is announcing its intent to solicit proposals under this Broad Agency Announcement (BAA) for the topic, Development of an Automated Driving System (ADS) National Strategy for the National Park Service (NPS) through the use of Pilots in an Operational Setting. This solicitation is being conducted in accordance with Federal Acquisition Regulation (FAR) 35.016 and 6.102(d)(2).

The purpose of this BAA is to conduct operational pilots of vehicle automation technologies (including Advanced Driver Assistance Systems [ADAS] and Automated Driving Systems [ADS]) at three national park units to inform potential long-term integration into parks’ remote transportation systems, to improve their efficiency and sustainability. The three selected units are Acadia National Park, Golden Gate National Recreation Area, and Yosemite National Park. See Appendix B – Statement of Objectives (SOO) for more details about each location.

This BAA is being evaluated in two Steps, see attached for more details:

Step 1 – Advisory Down Select. Interested offerors are required to submit Volume I White Paper no later than August 22, 2025. Failure to participate in Step 1 of the solicitation precludes further consideration of an Offeror.

Step 2 – Evaluation of Volumes II and III. Step 2 submission due date is October 3, 2025.

Program Solicitation: Heterogeneous Architectures for Quantum (HARQ) A

DARPA

Solicitation: DARPA-PS-25-31

https://sam.gov/workspace/contract/opp/944007d554364a1aad811469028a7e73/view

Posted Date: August 07, 2025

Proposal Due Date: October 14, 2025

The Defense Advanced Research Projects Agency (DARPA) is soliciting proposals towards the realization of heterogeneous quantum computing architectures. Proposed research should investigate innovative approaches that enable revolutionary advances in theory, devices, and system concepts for quantum interconnects, quantum circuit compilers, distributed algorithms, resource estimation, quantum memory/repeater devices, quantum frequency converters, microwave-to-optical transducers, and other elements at the intersection of hardware and software in the quantum computing stack. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice.

Missile Defense Agency – Advanced Capability Concepts

DOD

Solicitation: HQ0860-25-S-C001

https://sam.gov/workspace/contract/opp/6c8d1f82be50450291ecd5ab21406abc/view

Posted Date: August 07, 2025

Proposal Due Date: May 08, 2030

The Missile Defense Agency (MDA) Advanced Capability Concepts solicitation provides industry an ongoing opportunity to present the Government with new, unique and innovative ideas. This solicitation seeks innovative concepts, technological innovations, prototype demonstrations, and scientific breakthroughs that will significantly enhance the robustness and effectiveness of all Missile Defense System elements. White papers will be accepted any time during the five (5) year period of the solicitation. See attachments for full details.

Multi-Domain Force Applications and Traffic Management for Unmanned Aircraft Systems (M-FAT)

DOD

Solicitation: FA8750-25-S-7004

https://sam.gov/workspace/contract/opp/fc921bfba19241039572908fc7296c72/view

Posted Date: August 06, 2025

White papers Due Date: white papers will be considered if received prior to 3pm Eastern Standard Time (EST) on 4 AUG 2030

Only white papers will be accepted as initial submissions; formal proposals will be accepted by invitation only.

This announcement is for an Open, 2 Step BAA which is open and effective until 4 AUG 2030.  Only white papers will be accepted as initial submissions; formal proposals will be accepted by invitation only.  While white papers will be considered if received prior to 3pm Eastern Standard Time (EST) on 4 AUG 2030, the following submission dates are suggested to best align with projected funding:

FY26 by 05  SEP 2025

FY27 by 31 AUG 2026

FY28 by 31 AUG 2027

FY29 by 31 AUG 2028

FY30 by 31 AUG 2029

Offerors should monitor the Contract Opportunities on the SAM website at https://SAM.gov in the event this announcement is amended.

CONCISE SUMMARY OF TECHNOLOGY REQUIREMENT:

Seeking innovative research to enhance Counter-small Unmanned Aerial System (C-sUAS) kill chain and point defense capabilities through advancements in Electronic Warfare (EW), Cyberspace Operations (CO), Command and Control (C2) Automation and Autonomy, Low-Collateral Defeat (LCD), Low-Collateral Effect Interceptors (LCEI)/Blue Force Interceptors (BFI), and communications.

One goal is to blur the line between EW and CO by developing cyberspace countermeasures that disrupt sUAS operations, particularly command and control links. This includes improving system resiliency in contested environments and prioritizing low-collateral damage solutions. C2 advancements aim to automate and optimize responses to sUAS threats, especially swarm attacks, through AI/ML, sensor fusion, and automated decision-making. Research into LCD/LCEI/BFI could lead to the development of low-cost, autonomous interceptors with integrated EW/CO capabilities and other C-sUAS payloads.

Further research will focus on improving sensor technologies for enhanced detection, identification, and tracking, as well as developing a library for storing and indexing cyberspace effects. In parallel, efforts will be made to advance UAS Traffic Management (UTM) systems, integrating them with existing air traffic control, enabling safe integration of unmanned aircraft into the airspace.

Finally, communication systems will be enhanced through advanced modeling and simulation, development of resilient waveforms and networking protocols for swarm operations, and integration of AI for network optimization and spectrum management.

Test Bed: Toward a Network of Programmable Cloud Laboratories

NSF

Solicitation: 25-541

https://www.grants.gov/search-results-detail/360244

Posted Date: August 05, 2025

Proposal Due Date: November 20, 2025

Autonomous experimentation is poised to accelerate research and unlock critical scientific advances that bolster U.S. competitiveness and address pressing societal needs. Programmable Cloud Laboratories are able to execute automated workstreams, including self-driving lab workflows, to efficiently move research goals through artificial intelligence (AI) enabled experiment design, laboratory preparations, data collection, data analysis and interpretation. While limited-scale efforts have shown promise, versatile programmable and self-driving labs capable of addressing complex research questions with trustworthy results will require coordinated technological advances and an engaged research community. Additional challenges include the availability of automated laboratory infrastructure, standardized approaches to data collection for interoperability, advances in AI for data interpretation and experimental design, and more. This solicitation aims to address such gaps and realize the potential of autonomous experimentation. The Test Bed: Toward a Network of Programmable Cloud Laboratories (PCL Test Bed) program seeks to establish and facilitate the operation of distributed autonomous laboratory facilities. These laboratories will combine technological and human capacity to enable integration, testing, evaluation, validation, and translation of cutting-edge technology solutions in automated science and engineering. The PCL Test Bed will consist of a set of Programmable Cloud Laboratory Nodes (PCL Nodes) that can be remotely accessed to run custom workflows specified and programmed by users, that are linked together via computational networking, shared science questions, and data and artificial intelligence (AI) standards. The PCL Test Bed will facilitate access to advanced scientific equipment, accelerate translation and scaling of basic research into industry applications, enhance reproducibility and the exchange of experimental data, and assist in training the next generation of scientists and engineers in state-of-the art methodologies. It will help develop community norms, best practices, and formal standards for automated laboratory procedures, workflows, and instrument testing and validation. It will also advance consistent practices for the collection, sharing, and use of metadata and training data and the use and exploitation of AI methods. This program will also support the development of automated laboratory methods, including self-driving autonomous experiment workflows. Proposals must have a set of well-defined science drivers poised to derive significant benefit from targeted use of the PCL Test Bed capabilities, including but not limited to synthesis, optimization, and/or characterization experiments, in specific sub-disciplines within materials science, biotechnology, chemistry or other areas of science and engineering. These science drivers will guide the protocols and standards necessary for each node and facilitate collaboration across the Test Bed. For example, science drivers could include but are not limited to:

  • Materials science, materials synthesis and characterization efforts that advance U.S. competitiveness.
  • Biotechnology experiments in scalable, high-throughput engineering and characterization services for proteins or microbes with novel applications in the U.S. bioeconomy.
  • High-throughput experimentation for the accelerated development of catalysts to support more efficient chemical synthesis to address urgent national needs.

User Recruitment and On-Boarding Workshops will be a key component of the PCL Test Bed program and will serve to recruit users to individual PCL Nodes and the Test Bed to help make progress on the proposed science drivers, provide access to technology, test the limits of the experimental set-up of the nodes, and explore new research opportunities between the PCL Nodes and institutions including, but not limited to, R2 Universities, PUI (Primarily Undergraduate Institutions), and two-year institutions. The PCL Test Bed will be available to researchers in academia as well as industry, including current and former awardees from the Small Business Innovation Research/Small Business Technology Transfer (SBIR/STTR) programs. The portfolio of projects is available here,https://seedfund.nsf.gov/portfolio. PCL Nodes are expected to develop and implement plans for continued operation after the period of this award.

Agriculture and Food Research Initiative Competitive Grants Program Foundational and Applied Science Program

National Institute of Food and Agriculture/NIFA

Solicitation: USDA-NIFA-AFRI-011134

https://www.grants.gov/search-results-detail/360205

Posted Date: August 01, 2025

Proposal Due Date: December 31, 2026

This notice identifies the objectives for Agriculture and Food Research Initiative (AFRI) Foundational and Applied Science program projects, deadlines, funding information, eligibility criteria for projects and applicants, and application forms and associated instructions. AFRI is America’s flagship competitive grants program that provides funding for fundamental and applied research, education, and extension projects in the food and agricultural sciences. In this RFA, NIFA requests applications for the six AFRI priority areas through the FAS Program for FY 2026. The goal of this program is to invest in agricultural production research, education, and extension projects for more sustainable, productive, and economically-viable plant and animal production systems. It is imperative to develop innovative, safe, and sustainable management strategies for livestock (including poultry and aquaculture species), crops, and critical underlying resources.

In 2026, applications are sought in the following priority areas:
1. Plant health and production and plant products;
2. Animal health and production and animal products;
3. Food safety, nutrition, and health;
4. Bioenergy, natural resources, and environment;
5. Agriculture systems and technology; and
6. Agriculture economics and rural communities

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