The International Research Experiences for Students (IRES) program supports international research and research-related activities for U.S. science and engineering students. The IRES program contributes to development of a diverse, globally-engaged workforce with world-class skills. IRES focuses on active research participation by undergraduate or graduate students in high quality international research, education and professional development experiences in NSF-funded research areas. The overarching, long-term goal of the IRES program is to enhance U.S. leadership in research and education and to strengthen economic competitiveness through training the next generation of research leaders. This solicitation features three mechanisms; proposers are required to select one of the following tracks to submit their proposal. Track I focuses on the development of world-class research skills in international cohort experiences. Track II is dedicated to targeted, intensive learning and training opportunities that leverage international knowledge at the frontiers of research. Track III supports U.S. institutional collaborations to develop, implement and evaluate innovative models for high-impact, large-scale international research and professional development experiences for U.S. graduate students. Student participants supported by IRES funds must be citizens, nationals, or permanent residents of the United States. Students do not apply directly to NSF to participate in IRES activities. Students apply to NSF-funded investigators who receive IRES awards. To identify appropriate IRES projects, students should consult the directory of active IRES awards. All PIs, co-PIs and Senior Personnel on IRES proposals must be from U.S. based institutions.

NineSigma, on behalf of a global leader in the manufacture of high-value carbon products, invites proposals for novel, sustainable or recycling-derived feedstocks suitable for producing carbon black.

NineSigma, representing Equinor ASA, invites proposals for a method that permits the cost-effective installation of small sensors at the bottom (at 6 o'clock) of insulated pipes on an industrial scale (thousands of sensors). To install the sensor, a 16 mm wide hole needs to be made through a 0.6 mm thick stainless steel jacket. The purpose of the call is to find an innovative and  cost-effective alternative to manual installations that use scaffolding.

This program will increase technological investigative capacity and associated training for law enforcement and prosecutorial agencies. This solicitation will particularly focus on supporting the development, refinement, and advancement of widely used investigative tools, methods and technologies that address child pornography, exploitation and sex trafficking.

The purpose of this Funding Opportunity Announcement (FOA) is to build upon the work that has begun under previous FOA RFA-TR-17-007 "NCATS Pilot Program for Collaborative Drug Discovery Research Using Bioprinted Skin Tissue" and utilize physiologically relevant and validated 3-D biofabricated skin disease tissue models in multi-well drug screening platforms. The FOA will support intramural- extramural collaborations to implement the use of 3-D biofabricated skin tissue models and provide evidence of success for 3-D drug screening platforms.

The Materials Research Science and Engineering Centers (MRSECs) program provides sustained support of interdisciplinary materials research and education of the highest quality while addressing fundamental problems in science and engineering. Each MRSEC addresses research of a scope and complexity requiring the scale, synergy, and multidisciplinarity provided by a campus-based research center. The MRSECs support materials research infrastructure in the United States, promote active collaboration between universities and other sectors, including industry and international organizations, and contribute to the development of a national network of university-based centers in materials research, education, and facilities. A MRSEC may be located at a single institution, or may involve multiple institutions in partnership, and is composed of up to three Interdisciplinary Research Groups, IRGs, each addressing a fundamental materials science topic aligned with the Division of Materials Research, DMR.

NSF has long supported transformative research in artificial intelligence (AI) and machine learning (ML). The resulting innovations offer new levels of economic opportunity and growth, safety and security, and health and wellness. At the same time, broad acceptance of large-scale deployments of AI systems relies critically on their trustworthiness which, in turn, depends upon the collective ability to ensure, assess, and ultimately demonstrate the fairness, transparency, explainability, and accountability of such systems. Importantly, the beneficial effects of AI systems should be broadly available across all segments of society. NSF and Amazon are partnering to jointly support computational research focused on fairness in AI, with the goal of contributing to trustworthy AI systems that are readily accepted and deployed to tackle grand challenges facing society. Specific topics of interest include, but are not limited to transparency, explainability, accountability, potential adverse biases and effects, mitigation strategies, validation of fairness, and considerations of inclusivity. Funded projects will enable broadened acceptance of AI systems, helping the U.S. further capitalize on the potential of AI technologies. Although Amazon provides partial funding for this program, it will not play a role in the selection of proposals for award.

With the NSF Convergence Accelerator, NSF's goals are: (i) to pilot a new NSF capability to accelerate use-inspired convergence research in areas of national importance, and (ii) to initiate convergence team-building capacity around exploratory, potentially high-risk proposals in specific convergence topics (tracks). The NSF Convergence Accelerator supports use-inspired, goal-oriented, basic research, encouraging rapid advances through partnerships that include multiple stakeholders (e.g., industry, academic, not-for-profits, government entities, and others). The NSF Convergence Accelerator brings teams together in a cohort that are all focused on a common research goal of national importance, but which may be pursuing many different approaches. As a funder of research and education across all fields of science and engineering and with relationships with universities and funding agencies around the world, NSF is uniquely positioned to pilot this approach to accelerate discovery and innovation. Teams supported by the NSF Convergence Accelerator will focus on grand challenges that require a convergence approach. The teams are multidisciplinary and leverage partnerships; tracks within the NSF Convergence Accelerator relate to a grand challenge problem and have a high probability of resulting in deliverables that will benefit society within a fixed term. The NSF Convergence Accelerator is modeled on acceleration and innovation activities from the most forward-looking companies and universities. Specific funding opportunities will be announced through Dear Colleague Letters, program announcements, and/or solicitations. For more information see the NSF Convergence Accelerator website: https://www.nsf.gov/od/oia/convergence-accelerator/index.jsp

NSF's Harnessing the Data Revolution (HDR) Big Idea is a national-scale activity to enable new modes of data-driven discovery that will allow fundamental questions to be asked and answered at the frontiers of science and engineering. Through this NSF-wide activity, HDR will generate new knowledge and understanding, and accelerate discovery and innovation. The HDR vision is realized through an interrelated set of efforts in: Foundations of data science; Algorithms and systems for data science; Data-intensive science and engineering; Data cyberinfrastructure; and Education and workforce development. Each of these efforts is designed to amplify the intrinsically multidisciplinary nature of the emerging field of data science. The HDR Big Idea will establish theoretical, technical, and ethical frameworks that will be applied to tackle data-intensive problems in science and engineering, contributing to data-driven decision-making that impacts society. This solicitation describes one or more Ideas Lab(s) on Data-Intensive Research in Science and Engineering (DIRSE) as part of the HDR Institutes activity. These Ideas Labs represent one path of a conceptualization phase aimed at developing Institutes as part of the NSF investment in the HDR Big Idea.

The purpose of the RERC program is to improve the effectiveness of services authorized under the Rehabilitation Act by conducting advanced engineering research on and development of innovative technologies that are designed to solve particular rehabilitation problems or to remove environmental barriers. RERCs also demonstrate and evaluate such technologies, facilitate service delivery system changes, stimulate the production and distribution of new technologies and equipment in the private sector, and provide training opportunities. Field-Initiated RERC on Technology for People who are Deaf or Hard of Hearing: In this area, NIDILRR seeks to fund research and development that leads to innovative technological solutions and strategies to improve the accessibility, usability, and performance of technologies designed to benefit people who are deaf or hard of hearing.

The National Institute of Biomedical Imaging and Bioengineering (NIBIB) and VentureWell have come together to support and expand DEBUT, a competition that recognizes undergraduate excellence in biomedical design and innovation. DEBUT challenges teams of students in undergraduate biomedical education to solve real world problems in healthcare. Prizes of up to $20,000 will be awarded, with a total prize purse of $80,000. Strong DEBUT submissions will demonstrate a mastery of analytical and design skills and capabilities; the ability to manage the product development process; the ability to work effectively in teams; and technical communication skills. Submissions will be judged on the following criteria: Significance of the problem being addressed Impact of proposed solution on potential users and clinical care Innovative design Working prototype

In support of its mission, Zonta is inviting applications for its Amelia Earhart Fellowship from women of any nationality who are pursuing a PhD. Fellowships of $10,000 are awarded to thirty-five women each year and may be used at any university or college offering accredited postgraduate courses and degrees. The program aims to help talented women pursuing advanced studies in the typically male-dominated fields of aerospace-related sciences and engineering achieve their educational goals. The fellowship is intended to help these women invest in state-of-the-art computers to conduct their research, purchase expensive books and resource materials, and participate in specialized studies around the globe. Women of any nationality pursuing a PhD/doctoral degree who demonstrate a superior academic record in the field of aerospace-related sciences or aerospace-related engineering are eligible to apply. Applicants must be registered in a full-time PhD./doctoral program when funds are received in September and not be on track to graduate before April.

The Minerva Research Initiative (Minerva) emphasizes questions of strategic importance to U.S. national security policy. It seeks to increase the Department's intellectual capital in the social sciences and improve its ability to address future challenges and build bridges between the Department and the social science community. Minerva brings together universities and other research institutions around the world and supports multidisciplinary and cross-institutional projects addressing specific interest areas determined by the Department of Defense. The Minerva program aims to promote research in specific areas of social science and to promote a candid and constructive relationship between DoD and the social science academic community.

This Funding Opportunity Announcement (FOA) will provide funding to address the highest priority R&D areas within biofuel technologies, bioproducts, and biopower. It includes Areas of Interest (AOIs) from all five BETO programs: Feedstock Supply and Logistics; Advanced Algal Systems; Conversion; Advanced Development and Optimization; and Sustainability and Strategic Analysis. Each AOI supports BETO's objectives to reduce the minimum selling price of drop-in biofuels, lower the cost of biopower, enable high-value products from biomass or waste resources, and improve the quality of feedstock characterization and reliability of biorefinery operations. The full FOA is posted on the EERE Exchange website at https://eere-exchange.energy.gov. To apply to this FOA, Applicants must register with and submit application materials through EERE Exchange, EERE's online application portal. Information on where to submit questions regarding the content of the announcement and where to submit questions regarding submission of applications is found in the full FOA posted on the EERE Exchange website.

The U.S. Department of Energy's (DOE) Building Technologies Office (BTO) Advanced Building Construction with Energy-Efficient Technologies & Practices (ABC) FOA supports research and development of solutions that can be applied to many segments of the building sector, including existing and new buildings, residential and commercial, and across multiple climate zones. BTO is seeking applications aimed at developing deep energy retrofit and new construction technologies that holistically tackle a combination of envelope, heating, cooling, water heating, and ventilation issues, and hold appeal for both building owners and occupants. BTO is interested in three topic areas: Topic 1: Integrated Building Retrofits Topic 2: New Construction Technologies Topic 3: Advanced Technology Integration

NineSigma, representing a global leading autoparts manufacturer, seeks technologies for identifying and predicting the excitation force of motor-driven rotating machines and technologies for developing vibration transmission models. Specifically, the Client focuses on experimental identification and/or prediction method that are applicable to high frequency ranges (≤5 kHz) and have high accuracy in principle, as well as development of vibration transmission model.

NineSigma's client is a global supplier of high performance materials for a variety of high temperature applications. Transient liquids process relies on the liquid reaction with time leading to novel solid crystalline compounds at high temperatures. The transient liquid formed evaporates over time to leave pores enabling fast sintering within the bulk phase. Currently, NineSigma's client incorporates Boron source into Alumina compounds which forms the transient liquid at <1000 °C. The objective of the current search is to identify potential mineral additives that enable the formation of the transient liquids at lower temperatures and ideally below 700 °C. The client is open to all solutions from academia and industry.

Quantum Leap Challenge Institutes are large-scale interdisciplinary research projects that aim to advance the frontiers of quantum information science and engineering.  Research at these Institutes will span the focus areas of quantum computation, quantum communication, quantum simulation and/or quantum sensing.  The institutes are expected to foster multidisciplinary approaches to specific scientific, technological, educational workforce development goals in these fields.  Two types of awards will be supported under this program: (i) 12-month Conceptualization Grants (CGs) to support teams envisioning subsequent Institute proposals and (ii) 5-year Challenge Institute (CI) awards to establish and operate Quantum Leap Challenge Institutes. This activity is part of the Quantum Leap, one of the research Big Ideas promoted by the National Science Foundation (NSF). The NSF Quantum Leap Challenge Institutes program is consistent with the scope of NSF multidisciplinary centers for quantum research and education as described in the National Quantum Initiative Act [1].

A grand challenge in computing is the creation of machines that can proactively interpret and learn from data in real time, solve unfamiliar problems using what they have learned, and operate with the energy efficiency of the human brain. While complex machine-learning algorithms and advanced electronic hardware (henceforth referred to as 'hardware') that can support large-scale learning have been realized in recent years and support applications such as speech recognition and computer vision, emerging computing challenges require real-time learning, prediction, and automated decision-making in diverse domains such as autonomous vehicles, military applications, healthcare informatics and business analytics.