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NSF INCLUDES (Inclusion across the Nation of Communities of Learners of Underrepresented Discoverers in Engineering and Science) is a comprehensive national initiative designed to enhance U.S. leadership in science, technology, engineering, and mathematics (STEM) discoveries and innovations by focusing on broadening participation in these fields at scale. The vision of NSF INCLUDES is to catalyze the STEM enterprise to collaboratively work for inclusive change, which will result in a STEM workforce that reflects the population of the Nation. The initiative is developing a National Network composed of NSF INCLUDES Design and Development Launch Pilots, NSF INCLUDES Alliances, an NSF INCLUDES Coordination Hub, NSF-funded broadening participation projects, other relevant NSF-funded projects, scholars engaged in broadening participation research, and other organizations that support the development of talent from all sectors of society to build an inclusive STEM workforce.

As part of our commitment to building the field of data science for social impact, data.org has launched a $10 million data.org Inclusive Growth and Recovery Challenge. We are seeking inclusive growth proposals from and for anywhere in the world. We are particularly interested in the areas listed below - but welcome other proposals for using data science to advance shared prosperity, and help ensure an inclusive recovery. - Jobs of tomorrow - Access to capital - Cities and towns

As part of broader university-wide diversity and inclusion efforts, the Office of the President and the Office for the Advancement of Research and Scholarship (OARS) have issued a special call for proposals to conduct research, scholarship, or creative activities in the areas of social justice, human rights, diversity, and inclusion. Proposals may be submitted in any of these areas, but must address a scholarly question that will lead to testable objectives or measurable outcomes.

Inclusion across the Nation of Communities of Learners of Underrepresented Discoverers in Engineering and Science (NSF INCLUDES) is a comprehensive national initiative designed to enhance U.S. leadership in science, technology, engineering and mathematics (STEM) discoveries and innovations focused on NSF's commitment to diversity, inclusion, and broadening participation in these fields. The initiative is developing a National Network composed of NSF INCLUDES Design and Development Launch Pilots, NSF INCLUDES Alliances, NSF-funded broadening participation projects, other relevant NSF-funded projects, scholars engaged in broadening participation research, and other organizations that support the development of talent from all sectors of society to build the STEM workforce. To facilitate the Network's operation, the program is soliciting proposals for a NSF INCLUDES Coordination Hub that will drive and support the work of the NSF INCLUDES National Network over the lifecycle of the initiative by: (a) promoting the NSF INCLUDES guiding vision and strategy; (b) developing a collaborative infrastructure to support the activities of the various entities partnering in the NSF INCLUDES National Network; (c) fostering progress among Network partners toward shared models, measurement practices, and evaluation criteria; (d) communicating the discoveries of and generating enthusiasm for the NSF INCLUDES National Network; and (e) advancing the expansion and scale of the NSF INCLUDES National Network by connecting expertise from multiple sectors and other private and public funders.

As part of our commitment to building the field of data science for social impact, data.org has launched a $10 million data.org Inclusive Growth and Recovery Challenge. Any strong and growing economy requires an inclusive and resilient approach to growth to ensure that talent, innovation, and our communities can become stronger in times of stress. By tapping into the expertise of a broad pool of thinkers and doers, we aim to catalyze innovative and scalable solutions to help individuals and communities thrive, all the while building resilience to withstand future challenges.

The NSF ADVANCE program provides grants to enhance the systemic factors that support equity and inclusion and to mitigate the systemic factors that create inequities in the academic profession and workplaces. Systemic (or organizational) inequities may exist in areas such as policy and practice as well as in organizational culture and climate. For example, practices in academic departments that result in the inequitable allocation of service or teaching assignments may impede research productivity, delay advancement, and create a culture of differential treatment and rewards. Similarly, policies and procedures that do not mitigate implicit bias in hiring, tenure, and promotion decisions could lead to women and racial and ethnic minorities being evaluated less favorably, perpetuating historical under-participation in STEM academic careers and contributing to an academic climate that is not inclusive. All NSF ADVANCE proposals are expected to use intersectional approaches in the design of systemic change strategies in recognition that gender, race and ethnicity do not exist in isolation from each other and from other categories of social identity. The solicitation includes four funding tracks: Institutional Transformation (IT), Adaptation, Partnership, and Catalyst, in support of the NSF ADVANCE program goal to broaden the implementation of systemic strategies that promote equity for STEM faculty in academic workplaces and the academic profession.

The Best Buy foundation is seeking applications from nonprofit organizations for programs that provide youth with access to new technologies that help them become fluent in digital learning while developing the skills they need for future education and career success. Grants of up to $200,000 will be awarded for programs that utilize technology such as computers, digital cameras, video cameras, and professional software in a wide range of areas, including audio production (music mixing and recording), coding/3D printing, computer maintenance and repair, digital photography/graphic design filmmaking and videography, maker-faires and hack-a-thons, mobile and game app development, programming, robotics, and/ or website design. To be eligible, applicants must be a nonprofit organization with an existing out-of-school time program and a proven track record of serving youth between the ages of 13 and 18 in underserved communities. In addition, programs must operate within twenty-five miles of a Best Buy store or other Best Buy center of operation; have a commitment to diversity and inclusion; a willingness to integrate Geek Squad Academy curriculum into existing programming (if appropriate); and have the ability to conduct programming in multiple targeted sites across the country.

The Best Buy foundation is seeking applications from nonprofit organizations for programs that provide youth with access to new technologies that help them become fluent in digital learning while developing the skills they need for future education and career success. Grants of up to $200,000 will be awarded for programs that utilize technology such as computers, digital cameras, video cameras, and professional software in a wide range of areas, including audio production (music mixing and recording), coding/3D printing, computer maintenance and repair, digital photography/graphic design filmmaking and videography, maker-faires and hack-a-thons, mobile and game app development, programming, robotics, and/ or website design. To be eligible, applicants must be a nonprofit organization with an existing out-of-school time program and a proven track record of serving youth between the ages of 13 and 18 in underserved communities. In addition, programs must operate within twenty-five miles of a Best Buy store or other Best Buy center of operation; have a commitment to diversity and inclusion; a willingness to integrate Geek Squad Academy curriculum into existing programming (if appropriate); and have the ability to conduct programming in multiple targeted sites across the country.  

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

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.

In FY 2017, NSF is continuing a program aligned with the Improving Undergraduate STEM Education (IUSE) framework: REvolutionizing engineering and computer science Departments. This funding opportunity enables engineering and computer science departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome longstanding issues in their undergraduate programs and educate inclusive communities of engineering and computer science students prepared to solve 21st century challenges.

In FY 2017, NSF is continuing a program aligned with the Improving Undergraduate STEM Education (IUSE) framework: REvolutionizing engineering and computer science Departments. This funding opportunity enables engineering and computer science departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome longstanding issues in their undergraduate programs and educate inclusive communities of engineering and computer science students prepared to solve 21st century challenges.

This funding opportunity enables engineering and computer science departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome longstanding issues in their undergraduate programs and educate inclusive communities of engineering and computer science students prepared to solve 21st century challenges.

This funding opportunity enables engineering and computer science departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome longstanding issues in their undergraduate programs and educate inclusive communities of engineering and computer science students prepared to solve 21st century challenges.

EarthCube is a community-driven activity sponsored through a partnership between the NSF Directorate of Geosciences and Office of Cyberinfrastructure to transform the conduct of geosciences research and education. EarthCube aims to create a well-connected and facile environment to share data and knowledge in an open, transparent, and inclusive manner, thus accelerating the ability of the geosciences community to understand and predict the Earth system.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; or the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to involve the public health research community, including for example, epidemiologists, physicians, veterinarians, food scientists, social scientists, entomologists, pathologists, virologists, or parasitologists with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

This funding opportunity enables engineering departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome long-standing issues in their undergraduate programs and educate inclusive communities of engineering students prepared to solve 21st century challenges.  Computer science departments, whether administratively located in or outside an engineering program, are included in RED, as they share the same challenges as traditional engineering departments.

The NSF Engineering (ENG) Directorate is launching a multi-year initiative, the Professional Formation of Engineers, to create and support an innovative and inclusive engineering profession for the 21st Century.  Professional Formation of Engineers (PFE) refers to the formal and informal processes and value systems by which people become engineers.  It also includes the ethical responsibility of practicing engineers to sustain and grow the profession.  The engineering profession must be responsive to national priorities, grand challenges, and dynamic workforce needs; it must be equally open and accessible to all.

This funding opportunity enables engineering and computer science departments to lead the nation by successfully achieving significant sustainable changes necessary to overcome longstanding issues in their undergraduate programs and educate inclusive communities of engineering and computer science students prepared to solve 21^st-century challenges.

EarthCube is a community-driven activity sponsored through a partnership between the NSF Directorate for Geosciences (GEO)and the Directorate for Computer & Information Science & Engineering's (CISE) Office of Advanced Cyberinfrastructure (OAC)to transformresearch inthe academic geosciences community. EarthCube aims to create a well-connected and facile environment to share data and knowledge in an open, transparent, and inclusive manner, thus accelerating our ability to understand and predict the Earth system. Achieving EarthCube will requirea long-term dialog between NSF and the interested scientific communities to develop cyberinfrastructure that is thoughtfully and systematically built to meet the current and future requirements of geoscientists. New avenues will be supported to gather community requirements and priorities for the elements of EarthCube, and to capture the best technologies to meet these current and future needs. The EarthCube portfolio will consist of interconnected projects and activities that engage the geosciences, cyberinfrastructure, computer science, and associated communities. The portfolio of activities and funding opportunities will evolve over time depending on the status of the EarthCube effort and the scientific and cultural needs of the geosciences community. This umbrella solicitation for EarthCube allows funding opportunities to be flexible and responsive to emerging needs and collaborative processes. The EarthCube vision and goals do not change over time, and this section of the solicitation will remain constant. Funding opportunities to develop elements of the EarthCube environment will be described in Amendments to this solicitation. Amendments will appear in the Program Description section of the solicitation and will include details on the parameters, scope, conditions, and requirements of the proposal call. Researchers who receive alerts related to solicitation releases will receive notification when the EarthCube solicitati

The New Era of University Innovation & Commercialization This panel discussion examines the future of university and business collaboration, with a focus on inclusive innovation. Thursday, April 19, 2018 from 3:30 PM to 4:45 PM (EDT) Oxford, OH

The purpose of NIDILRR's Disability and Rehabilitation Research Projects (DRRP), which are funded through the Disability and Rehabilitation Research Projects and Centers Program, is to plan and conduct research and dissemination and utilization activities to develop methods, procedures, and rehabilitation technology that maximize the full inclusion and integration into society, employment, independent living, family support, and economic and social self-sufficiency of individuals with disabilities, especially individuals with the most severe disabilities, and to improve the effectiveness of services authorized under the Rehabilitation Act of 1973, as amended (Rehabilitation Act). The purposes of this particular DRRP are to conduct rigorous research, development, technical assistance, dissemination, and utilization activities to increase successful technology transfer of rehabilitation technology products and devices developed by NIDRR-funded technology grantees.

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in making research data and artificial intelligence (AI) models findable, accessible, interoperable, and reusable (FAIR1) to facilitate the development of new AI applications in SC's congressionally authorized mission space, which includes the advancement of AI research and development. In particular, ASCR is interested in supporting FAIR benchmark data for AI; and FAIR frameworks for relating data and AI models. For this FOA, AI is inclusive of, for example, machine learning (ML), deep learning (DL), neural networks (NN), computer vision, and natural language processing (NLP). Data, in this context, are the digital artifacts used to generate AI models and/or employed in combination with AI models during inference. An AI model is an inference method that can be used to perform a "task," such as prediction, diagnosis, or classification. The model is developed using training data or other knowledge. An AI task is the inference activity performed by an artificially intelligent system.