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Machine Learning and Artificial Intelligence (AI) are enabling extraordinary scientific breakthroughs in fields ranging from protein folding, natural language processing, drug synthesis, and recommender systems to the discovery of novel engineering materials and products. These achievements lie at the confluence of mathematics, statistics, engineering and computer science, yet a clear explanation of the remarkable power and also the limitations of such AI systems has eluded scientists from all disciplines. Critical foundational gaps remain that, if not properly addressed, will soon limit advances in machine learning, curbing progress in artificial intelligence. It appears increasingly unlikely that these critical gaps can be surmounted with increased computational power and experimentation alone. Deeper mathematical understanding is essential to ensuring that AI can be harnessed to meet the future needs of society and enable broad scientific discovery, while forestalling the unintended consequences of a disruptive technology. The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and Social, Behavioral and Economic Sciences (SBE) will jointly sponsor research collaborations consisting of mathematicians, statisticians, computer scientists, engineers, and social and behavioral scientists focused on the mathematical and theoretical foundations of AI. Research activities should focus on the most challenging mathematical and theoretical questions aimed at understanding...

This Notice of Funding Opportunity (NOFO) invites applications from clinical centers to participate in a consortium to test anti-obesity medication (AOM) treatment strategies for youth with obesity that maximize benefits and minimize risks of AOM use. Such intervention strategies should support the promotion of healthy growth and development; adequate nutritional status/intake, healthy eating and physical activity behaviors; mental health and well-being (e.g., body image, self-esteem, mood, etc.), and quality of life and be feasible to implement in clinical care settings. Priority areas include testing strategies to determine optimal developmental stage for AOM initiation, rate and amount of weight loss, AOM class, dose, frequency, and duration, and content and intensity of adjunct lifestyle therapies that may be imperative to ensure normal psychological and physical development and to potentially avoid lifelong dependence on AOMs. Investigators should also evaluate potential predictors of response/ nonresponse to various treatment strategies under evaluation. The clinical centers may conduct independent or multicenter trials but will collaborate on the development of protocols, use of common measures and data elements, use of a central laboratory and standardized procedures to collect data and biospecimens, and data analyses and manuscripts. This NOFO uses a cooperative agreement mechanism (U01) and runs in parallel with a companion NOFO (RFA-DK-27-136).

This Notice of Funding Opportunity (NOFO) invites applications for a Research Coordinating Center (RCC) to participate in a consortium of clinical centers that will test anti-obesity medication (AOM) treatment strategies for youth with obesity that maximize benefits and minimize risks of AOM use. Such intervention strategies should support the promotion of healthy growth and development; adequate nutritional status/intake, healthy eating and physical activity behaviors; mental health and well-being (e.g., body image, self-esteem, mood, etc.), and quality of life and be feasible to implement in clinical care settings. Priority areas include testing strategies to determine optimal developmental stage for AOM initiation, rate and amount of weight loss, AOM class, dose, frequency, and duration, and content and intensity of adjunct lifestyle therapies that may be imperative to ensure normal psychological and physical development and to potentially avoid lifelong dependence on AOMs. Investigators should also evaluate potential predictors of response/ nonresponse to various treatment strategies under evaluation. The clinical centers may conduct independent or multicenter trials but will collaborate on the development of protocols, use of common measures and data elements, use of a central laboratory and standardized procedures to collect data and biospecimens, and data analyses and manuscriptsThe RCC will lead, manage, and harmonize efforts for the Consortium including 1) providing management and administrative support; 2) providing leadership and expertise on statistical design a...

The overarching goal of this notice of funding opportunity (NOFO) and its companion opportunities is to establish the Precision Medicine with AI: Integrating Imaging with Multimodal Data (PRIMED-AI) Program to support development of innovative, reliable, cost-effective, and sustainable multimodal AI-based clinical decision support (CDS) tools. PRIMED-AI CDS tools are based on the integration of clinical imaging with other types of multimodal health data to enhance care for patients with a wide range of health conditions. The PRIMED-AI Program seeks to catalyze the adoption of AI-based CDS tools into clinical workflows to enable novel personalized medicine strategies that address significant health challenges. The purpose of this NOFO is to solicit applications for the design, development, and preliminary validation of robust frameworks for the application of multimodal-artificial intelligence (AI) models for clinical use. Frameworks developed through these awards would populate a "playbook", defined as a collection of actionable guidelines, standardized protocols, and/or standard operating procedures (SOPs) for reliable and effective development and deployment of multimodal AI tools. It is expected that the frameworks delineated in this playbook will directly address PRIMED-AI objectives and needs, while also remaining flexible enough to enable sufficient extensibility and interoperability for use across a broad spectrum of multimodal biomedical AI applications, both internal and external to the PRIMED-AI Program.

Buyer: Syndicat Martiniquais de Traitement et de Valorisation des Déchets | Notice type: cn-standard | Procedure: restricted | Contract: supplies | Deadline: 2026-10-10

The purpose of this notice of funding opportunity (NOFO) is to elucidate the key components of the therapeutic effects of rapid-acting psychotropic interventional drugs (RAPIDs) by addressing the methodological challenges involved with these clinical trials. In addition, this NOFO seeks to advance understanding of how RAPIDs and adjunctive psychosocial interventions can be optimally delivered, monitored, and sustained over time to enhance effectiveness and generalizability. The NOFO will support studies designed to enhance the rigor of RAPID clinical trial design, which will ultimately increase the interpretability of the data and the generalizability of the results.

Buyer: Rijksvastgoedbedrijf | Notice type: cn-standard | Procedure: open | Contract: works | Deadline: 2026-10-12

Buyer: Ministère de l'Économie, des Finances et de la Souveraineté industrielle, énergétique et numérique | Notice type: cn-standard | Procedure: oth-single | Contract: works | Deadline: 2026-10-12

Buyer: Gemeente Maastricht | Notice type: cn-standard | Procedure: oth-mult | Contract: services | Deadline: 2026-10-12

Expected Outcome:Make safer and more sustainable alternatives to substances of concern available to the industries offering products with targeted performances and supporting their competitiveness,Speeding up the innovation cycle within a value chain important for European industry;Enhancing competitiveness of the industries by reducing regulatory and operational costs, while making supply chains more secure;Production processes, chemicals, materials and products that are inherently safer and more sustainable for a clean and autonomous economy; andDemonstrating how the safe and sustainable by design (SSbD) chemicals and materials framework can guide innovation and encourage innovators to minimise the use of substances of concern, reducing negative impacts on human health, climate and ecosystems. Scope:The focus of this topic is on alternatives for the substitution of substances of concer...

Expected Outcome:Projects are expected to contribute to the following outcomes:To develop and demonstrate innovative AI-driven solutions in materials and process development to enhance the competitiveness and sustainability of the process industries by better products and process technologies and reducing the time to marketTo increase the competitiveness of materials production in Europe by AI-supported optimal operation of plants and value networks and early detection of problems and failuresTo improve the working conditions in the plants by using AI technologies, metaverse, and robots. Scope:Drastically improved AI methods and technologies hold transformative potential for the process industries, enabling advancements in process design, operational efficiency, and faster innovation across the entire lifecycle of plants and products. By using different AI approaches such as multimodal g...

Expected Outcome:Increased competitiveness and productivity, through innovative AI-enabled advanced manufacturing processes and operations, including real-time monitoring and adaptive optimisation; andReduction of emissions and alignment with Clean Industrial Deal objectives. Scope:AI approaches in manufacturing processes hold the potential to significantly enhance circularity, process and operational efficiency as well as sustainability of modern factories. Current state-of-the-art technologies have already paved the way for more streamlined operations, yet there remains untapped value in e.g. quality improvement, definition of optimal process operating conditions, reduction of scrap, optimization of energy usage. Real-time monitoring and adaptive optimisation using AI models can enable agile responses to production variability and support sustained, high-performance operations.New solu...

Expected Impact:Projects are expected to deliver results aligned with the expected results set out in this call topic and to evidence their contribution through dedicated KPIs defined in the proposal. Expected results include: • demonstrable and sustainable increase in production capacity for the targeted ammunition, bombs and missiles production lines, enabled by operational joint filling plants and production lines; • measurable reduction of production lead time from order/production decision to delivery in UA; • improved timely availability and supply of defence products for UA, including increased delivery reliability and readiness of production lines; • effective cross-border cooperation between UA and EU that enables production ramp-up, qualification, integration and sustainment. Proposals shall define, baseline and track KPIs such as: filling throughput (e.g., units/month or tonne...

Expected Impact:The results of the activities should contribute to support common procurement, leading to strengthening the cooperation among Member States and associated countries, as well as to greater interoperability. Furthermore, they should contribute to the building up of strategic stockpile of ammunition, missiles, including their components, or to the increase of existing ones, as well as to the development of low-cost unmanned systems for guided strikes adapted to modern warfare scenarios.Objective:This topic aims at actions supporting the common procurement of ammunition (including small arms ammunition, tank and anti-tank ammunitions, artillery ammunition, guided ammunitions), missiles (all types of missiles) and other explosive weapons (including hand grenade, land and naval mines, mortar, rockets, unmanned systems (aerial, ground, surface and underwater vehicles controlled...

Expected Impact:The results of the activities should contribute to support common procurement, leading to strengthening the cooperation among Member States and associated countries, as well as to greater interoperability. Furthermore, they should contribute to the replenishment of depleted stockpiles of counter-drone systems, to the increase of existing stockpiles or to establishment of defence industrial readiness pool, as well as to the development and reinforcement of counter-drone solutions as drones are being increasingly perceived as a pressing threat.Objective:This topic aims at actions supporting the common procurement of integrated systems (e.g. VSHORAD or SHORAD) or parts thereof (including sensors, kinetic or non-kinetic effectors - including direct energy weapons -, command and control solutions) to counter unmanned aerial, ground, surface or underwater vehicles, including th...

Expected Outcome:Project should contribute to all of the following expected outcomes:Research funders, policymakers and research communities in the social sciences and humanities (SSH) are provided with a multi-annual R&I programme on social transformations and resilience, responding to megatrends like climate change and biodiversity loss, digitalisation, demographic changes and unexpected shocks.Research investments on social protection and essential services, future of work, education and skills, and a fair transition to climate neutrality are increased.Stakeholders, including social partners and civil society, and policymakers are provided with evidence-based knowledge, tools and innovative solutions, which contribute to new policies and strategies for strengthening resilience, fairness, inclusiveness and social cohesion at European, national and regional level. Scope:Europe is underg...

Buyer: Gemeente Lochem | Notice type: cn-standard | Procedure: open | Contract: services | Deadline: 2026-10-13

Buyer: Louth and Meath Education and Training Board 1384 | Notice type: cn-standard | Procedure: open | Contract: services | Deadline: 2026-10-13

Buyer: "De Haagse Scholen", stichting voor primair en speciaal openbaar onderwijs | Notice type: cn-standard | Procedure: open | Contract: services | Deadline: 2026-10-14

Buyer: Comune di Caltanissetta - Direzione Urbanistica - Pianificazione Territoriale - SITR - Ambiente e Energia - Viabilità e Verde Pubblico | Notice type: cn-standard | Contract: services | Deadline: 2026-10-14

Buyer: Stadtwerk am See GmbH & Co.KG | Notice type: cn-standard | Procedure: open | Contract: works | Deadline: 2026-10-14

The Mathematical Biology Program supports research in all areas of mathematical sciences with relevance to the biological sciences. Successful proposals must demonstrate mathematical innovation, biological relevance and significance, and strong integration between mathematics and biology. Some projects of interest to the Mathematical Biology Program may include development of mathematical theories, methodologies, and tools traditionally seen in other disciplinary programs within the Division of Mathematical Sciences. In general, if a proposal is appropriate for review by more than one NSF program, it is advisable to contact the program officers handling each program to determine when and where the proposal should be submitted and to facilitate the review process. The Mathematical Biology Program regularly seeks joint reviews of proposals with programs in the Directorates of Biological Sciences and other relevant programs. Investigators are encouraged to discuss their project with program officers in relevant areas to determine whether it could be considered by more than one program. Research in Undergraduate Institutions (RUI) Investigators submitting an RUI proposal should read the RUI solicitation (link below), as the rules for proposal format may deviate from the Proposal & Award Policies & Procedures Guide (PAPPG). EAGER and RAPID Proposals Prior to submitting proposals for EArly-concept Grants for Exploratory Research (EAGER) or Rapid Response Research (RAPID), Investigators must contact the cognizant program directors. Requests for Award Supplements Principal Investig...

The Research Experiences for Teachers (RET) in Engineering and Computer Science program supports authentic summer research experiences for K-14 educators to foster long-term collaborations between universities, community colleges, school districts, and industry partners. With this solicitation, the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE) focus on a reciprocal exchange of expertise between K-14 educators and research faculty and (when applicable) industry mentors. K-14 educators will enhance their scientific disciplinary knowledge in engineering or computer science and translate their research experiences into classroom activities and curricula to broaden their students’ awareness of and participation in computing and engineering pathways. At the same time, the hosting research faculty will deepen their understanding of classroom practices, current curricula, pedagogy, and K-14 educational environments.

The purpose of the NCI Pathway to Independence Award for Early-Stage Postdoctoral Researchers (K99/R00) program is to increase and maintain a strong cohort of new and talented, NCI-supported, independent investigators. This program is designed for postdoctoral fellows with research and/or clinical doctoral degrees who do not require an extended period of mentored research training beyond their doctoral degrees. The objective of this award is to facilitate a timely transition of these fellows from their mentored, postdoctoral research positions to independent tenure-track (or equivalent) faculty positions. The program will provide independent NCI research support during this transition to help awardees to launch competitive, independent research careers. Researchers in the scientific areas of cancer control, cancer prevention and cancer data sciences are especially encouraged to work with their institutions to apply. This Notice of Funding Opportunity (NOFO) is designed specifically for candidates proposing research that does not involve leading an independent clinical trial, a clinical trial feasibility study, or an ancillary clinical trial. Under this NOFO candidates are permitted to propose a research experience in a clinical trial led by a mentor or co-mentor. Those proposing a clinical trial or an ancillary clinical trial as lead investigator, should apply to the companion NOFOs (PAR-23-287 or PAR-23-288).

The purpose of the NCI Pathway to Independence Award for Early-Stage Postdoctoral Researchers (K99/R00) program is to increase and maintain a strong cohort of new and talented, NCI-supported, independent investigators. This program is designed for postdoctoral fellows with research and/or clinical doctoral degrees who do not require an extended period of mentored research training beyond their doctoral degrees. The objective of this award is to facilitate a timely transition of these fellows from their mentored, postdoctoral research positions to independent tenure-track (or equivalent) faculty positions. The program will provide independent NCI research support during this transition to help awardees to launch competitive, independent research careers. Researchers in the scientific areas of cancer control, cancer prevention and cancer data sciences are especially encouraged to work with their institutions to apply. This notice of funding opportunity (NOFO) is designed specifically for candidates proposing to serve as the lead investigator of an independent clinical trial, a clinical trial feasibility study, or a separate ancillary clinical trial, as part of their research and career development. Those not planning an independent clinical trial, or proposing to gain research experience in a clinical trial led by another investigator, must apply to the 'Independent Clinical Trial Not Allowed' companion NOFO (PAR-23-286).