STEM K-12 supports research and development that measurably improves how students and teachers engage with STEM in preK-12, emphasizing rigorous evidence, practical implementation in real settings (classrooms, districts, informal learning), and broadening participation. Priority areas include learning progressions and assessments in computing/AI/data science, teacher professional learning tied to standards, design and study of learning technologies (e.g., intelligent tutoring, AR/VR, data dashboards), cybersecurity and data science pathways, and equity-centered approaches that scale to diverse communities. Proposals are accepted at any time; budgets/durations are expected to match project scope and evaluation rigor.
Focus areas aligned to UNO CIST
Computing Education & AI literacy: Design and study of K-12 CS/CT/AI curricula, assessments, and teacher PD; rigorous evaluation of learning outcomes (CS, CS Ed, ISQA Analytics).
Human-Centered Computing & Learning Tech: Intelligent tutors, AR/VR for inquiry, data-driven feedback dashboards, accessibility and inclusive design (CS HCC; IT Innovation).
Cybersecurity & Data Science for K-12: Secure lab experiences, competitions, curricular modules, PD for teachers, and impact studies (Cybersecurity; MS Data Science).
Health/Bioinformatics pipelines: Intro units and career-connected learning using authentic datasets; partnerships with local health orgs (BIOI/BMI; Health Informatics in ISQA).
Equity & broadening participation: Co-design with schools/communities in rural and underserved areas; research on implementation and scale-up strategies (cross-CIST).
Award summary:
Estimated Number of Awards: 40
Anticipated Funding Amount: $30,000,000
Suggested ranges for funding requests of STEM K-12 proposals under this solicitation are as follows: (1) Research and/or Development proposals: $350,000 to $750,000 with a duration of two to three years; and (2) Conference proposals: $25,000 to $99,000 with a duration of up to two years.
CHE supports fundamental discovery and tool/instrument development in chemical sciences, including: data-driven discovery and novel instrumentation; advanced analytics/AI for growing volumes and varieties of chemical data; environmental chemical processes; nanoscale/quantum-regime studies; theory/computation/modeling.
Research Directions of Particular Interest to CIST (drawn from solicitation scope; examples below show where CIST could collaborate/lead on the computing side):
Data discovery science & AI in chemistry: ML/AI methods for reaction prediction, spectroscopy/image analysis, catalyst design, and high-throughput screening (aligns with CIST AI, ML, data analytics).
Chemical Measurement & Imaging (CMI): Algorithms, sensing, and computational imaging pipelines (CIST strengths in systems, software engineering, HCC). (Program included in this solicitation list.)
Environmental Chemical Sciences (ECS): Modeling/analytics for complex environmental chemical datasets (CIST data science/MS programs).
Macromolecular/Supramolecular/Nanochemistry (MSN): Materials informatics and simulation workflows (CIST computing systems/software).
Focus areas aligned to UNO CIST
Data discovery science & AI in chemistry: ML/AI methods for reaction prediction, spectroscopy/image analysis, catalyst design, and high-throughput screening (aligns with CIST AI, ML, data analytics).
Chemical Measurement & Imaging (CMI): Algorithms, sensing, and computational imaging pipelines (CIST strengths in systems, software engineering, HCC). (Program included in this solicitation list.)
Environmental Chemical Sciences (ECS): Modeling/analytics for complex environmental chemical datasets (CIST data science/MS programs).
Macromolecular/Supramolecular/Nanochemistry (MSN): Materials informatics and simulation workflows (CIST computing systems/software).
Award summary:
Estimated number of awards: ~245 (subject to funds)
Anticipated total funding: ~$105,000,000 for new and continuing awards (subject to funds)
Proposal deadline: Phase 1, Sept. 30, 2025 (Phase 2 only open to Phase 1 winners)
DOE’s Round 3 aims to accelerate the electric sector’s digital transformation at the grid edge—advancing data analytics, digital systems, and resource integration in partnership with an energy-sector organization. Projects address two parallel tracks—resource integration under uncertainty and sensors/datasets for inverter-based resources & large loads—with an added emphasis this round on resilience to extreme events (e.g., wildfire, ice storms, hurricanes). Submissions must partner with a U.S. energy-sector entity, articulate a credible implementation path, and omit CII, identified cyber vulnerabilities, proprietary business information, and real datasets in the package. DOE intends for results to be shared as exemplars for the broader sector.
Focus areas aligned to UNO CIST
AI/Analytics for uncertainty & resilience: Uncertainty-aware modeling for operations/planning; risk-informed decision tools for extreme events (Track 1).
Sensing + data engineering: Methods that combine SCADA, synchrophasors, weather, wildfire risk, and other heterogeneous sources; creation of public research datasets (Track 2).
Human-centered tools & platforms: Dashboards, decision support, and workflows that utilities can adopt—validated with a named energy-sector partner.
Cyber-aware digital interconnectivity: Approaches mindful of modern, connected energy management ecosystems (DERs, EVSE, etc.).
Award summary:
Total prize pool: $2.5M across two tracks plus a bonus prize.
Track 1 – Resource Integration Under Uncertainty
Plan phase: Up to 8 awards, $75,000 each.
Progress phase: Up to 3 awards, $200,000 each.
Track 2 – Sensors & Datasets for IBRs and Large Loads
Plan phase: Up to 8 awards, $75,000 each.
Progress phase: Up to 3 awards, $200,000 each.
Bonus prize – Extremes Applications: Up to $100,000 total; eligible only to Plan-phase winners.
This Dear Colleague Letter (DCL) seeks to advance the goals of the Executive Order on Advancing Artificial Intelligence Education for American Youth by providing resources for K-12 AI education. To advance the goals of the executive order, NSF will accept supplemental funding proposals from existing awardees with K-12 AI or computer science education experience to refine, scale, evaluate, and/or implement established K-12 activities. Further information about eligible awardees specific to their NSF Directorate can be found at the end of this DCL. Supplement proposals should be for specific and focused educational efforts at the K-12 level that address age-appropriate AI education/literacy, and/or the use of technologies in AI education to facilitate adoption by educational partners. Activities with the potential to be implemented in classrooms within 12 months of the supplement award date will be prioritized for funding.
The proposed efforts should align with one or more of the following themes:
Theme 1: Teacher professional development — extend capacity and reach of teacher professional development programs for AI education that equip K-12 teachers to incorporate AI education into their existing lesson plans/curricula and/or prepare teachers to offer new AI course content or classes.
Theme 2: Curricula and instructional materials — refine, evaluate, and/or scale activities for K-12 students that cover AI topics and/or that provide instruction on how to use specific AI tools to solve real-world challenges. Materials should be connected to particular AI concepts, essential knowledge and/or skills, and tied to a specific grade level.
Theme 3: Technology and tools — refine, evaluate, and/or scale infrastructure, tools, or services that bring AI into the K-12 classroom or in other instructional settings to improve teaching and learning in any subject.
Theme 4: Networks — design/develop/expand organizational structures that provide resources and facilitate communication, collaboration, and knowledge sharing for AI education among researchers and K-12 education practitioners within and across their communities.
This Dear Colleague Letter (DCL) invites supplemental funding requests from current ExLENT and ATE awardees to pilot, implement, or expand AI-focused career and skill building learning opportunities for high school students. Supplemental funding requests will support activities led by ExLENT or ATE PIs including curriculum development, dual enrollment, micro-credentials, or hands-on experiential learning. Collaborations between ExLENT and ATE PIs are strongly encouraged. Proposals must include both community colleges and high schools, and must also involve industry partners to build integrated, career-connected AI education pathways for high school students.
Proposal deadline: LOI (Vision Statement) October 16, 2025
The Simons Foundation is seeking brief vision statements (LOIs) to surface bold, cross-disciplinary breakthrough areas at the interface of ecology and evolution. Proposed collaborations should target basic principles of ecological and evolutionary dynamics, integrate multiple levels and scales (genes→species→communities; local→global; ecological↔evolutionary time), and bring diverse methods and disciplines together. Emphasis is on high-risk, idea-generating research that may be overlooked by other funders. Teams are expected to openly share data, code, pipelines, protocols and reagents, include multiple seniority levels, and articulate why Simons’ collaborative model is uniquely enabling and timely for the topic.
CIST-aligned focus highlights:
Computational & Data-Driven Ecology/Evolution: Statistical/AI models of population, community, and ecosystem dynamics; multi-scale simulations; network and agent-based modeling (CS; Data Science; ISQA Analytics).
Bioinformatics & Genomics at Scale: Analyses linking genetic/omic variation to ecological/evolutionary processes; reproducible pipelines; open data practices (Bioinformatics; Biomedical Informatics).
Sensing, Informatics & HCC: Integrating heterogeneous datasets (e.g., environmental, imaging, citizen science), usability and collaboration platforms for distributed teams (IT Innovation; HCC within CS programs).
Cyberinfrastructure & Secure Data Sharing: Scalable, secure workflows for cross-institutional collaboration and open-science requirements (Cybersecurity; ISQA).
Emphasis: Cross-disciplinary teams spanning methods, fields, and geographies; integration across biological and spatiotemporal scales; open sharing of all research products.
Structure: Initial vision statement; 10–20 spokes-PIs invited to submit full proposals. Finalists may present to the review committee prior to selection.
Award summary:
Total program budget: $8M/year to support 1–3 new Collaborations.
Per-collaboration: $1–4M/year, including 20% indirect costs.
Project period: 5 years, with potential for one renewal.
The 2026 funding opportunity is designed to facilitate research on integrating AI in courses—spanning effectiveness, ethics, pedagogy, and student experience.
Proposals must request funds for research that hopes to improve teaching by making significant,transformative changes to the design, pedagogy, learning materials, or special supports associated with existing courses. The proposed project may involve one faculty member or a team; Co-PIs may be from the same campus or skills might be leveraged by using expertise from faculty on other campuses. No funding can be awarded to those outside the NU System. If the PI does not have research experience, it is highly recommended an experienced Co-PI or research mentor be included in the proposal. Proposals related to general education or discipline-based courses will be considered.
Proposals impacting larger numbers of students will be given priority.
Award Summary
Up to $75,000 total for two or three years, with an expectation that the campus, college, and/or department provide an additional $25,000 for a total of $100,000.
UNO ORCA
Proposal deadline: Rolling while funds available. Submissions open September 15, 2025
The University Committee on Research and Creative Activity (UCRCA) expands the capacity for research and creative activity at UNO. The UCRCA makes funding recommendations to the Associate Vice Chancellor for Research and Creative Activity in a fair and transparent way.
OPTIONAL (but encouraged) pre-submission to subcommittees for constructive feedback.
All faculty applying for full UCRCA awards are strongly encouraged to use the pre-submission process before applying through NuRamp.
Eligibility: All areas, types and disciplines of research and creative activity by pre- and post- tenured faculty and graduate and undergraduate students at UNO.
The University of Nebraska does not discriminate based on race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation in its education programs or activities, including admissions and employment. The University prohibits any form of retaliation taken against anyone for reporting discrimination, harassment, or retaliation for otherwise engaging in protected activity.
