OARS funding Math & Statistics

Pre-release of the latest topics in the Air Force's SBIR and STTR Commercial Solutions Opening program, which include COVID-19 pandemic materials and manufacturing advances, human performance and medical response advances/solutions and information sciences' advances/solutions

The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is sponsoring a Proposers Day webcast to provide information to potential proposers on the objectives of an anticipated Research Announcement (RA) for the Young Faculty Award Program 2021 (YFA 2021) program. The Proposers Day will be held via prerecorded webcast on September 25, 2020 from 1:00 PM to 3:00 PM. Advance registration is required for viewing the webcast.

The Acquisition Research Program (ARP) (www.acquisitionresearch.net) conducts and supports research in academic disciplines that bear on public procurement policy and management. These include economics, finance, financial management, information systems, organization theory, operations management, human resources management, risk management, and marketing, as well as the traditional public procurement areas such as contracting, program/project management, logistics, test and evaluation and systems engineering management. The ARP is interested in innovative proposals that will provide unclassified and non-proprietary findings suitable for publication in open scholarly literature. Studies of government processes, systems, or policies should also expand the body of knowledge and theory of processes, systems, or policies outside the government. The following research areas are of special interest: Leading-edge techniques in data collection, management, visual analytics and decision-making; Robust risk modeling techniques; Performance metrics and methodologies; Collaboration and cross-functional teams; and, Model-Based Acquisition. Offerors bear prime responsibility for the design, management, direction and conduct of research. Researchers should exercise judgment and original thought toward attaining the goals within broad parameters of the research areas proposed and the resources provided. Offerors are encouraged to be creative in the selection of the technical and management processes and approaches and consider the greatest and broadest impact possible.

The primary aim of the Mathematical Sciences Infrastructure Program is to foster the continuing health of the mathematical sciences research community as a whole. In addition, the program complements the Workforce Program in the Mathematical Sciences in its goal to increase the number of well-prepared U.S. based individuals who successfully pursue careers in the mathematical sciences and in other professions in which expertise in the mathematical sciences plays an increasingly important role. The DMS Infrastructure program invites projects that support core research in the mathematical sciences, including: 1) novel projects supporting research infrastructure across the mathematical sciences community; 2) training projects complementing the Workforce Program, and 3) conference, workshop, and travel support requests that include cross-disciplinary activities or have an impact at the national scale. See below for more information about each category.

The CDS&E-MSS program accepts proposals that engage with the mathematical and statistical challenges presented by (1) the ever-expanding role of computational experimentation, modeling, and simulation on the one hand, and (2) the explosion in production and analysis of digital data from experimental and observational sources on the other. The goal of the program is to promote the creation and development of the next generation of mathematical and statistical software tools, and the theory underpinning those tools, that will be essential for addressing these challenges. The research supported by the CDS&E-MSS program will aim to advance mathematics or statistics in a significant way and will address computational or big-data challenges. Proposals of interest to the program must include a Principal Investigator or co-Principal Investigator who is a researcher in an area supported by the Division of Mathematical Sciences. The program welcomes submission of proposals that include multidisciplinary collaborations or provide opportunities for training through research involvement of junior mathematicians or statisticians. This program is part of the wider NSF Computational and Data-enabled Science and Engineering (CDS&E) enterprise.

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

The Laura Bassi Scholarship was established by Editing Press in 2018 with the aim of providing editorial assistance to postgraduates and junior academics whose research focuses on neglected topics of study, broadly construed, within their disciplines.

In consideration of the challenges facing many in our country, NSF is extending the upcoming proposal deadline for the Faculty Early Career Development Program (CAREER) until 5:00 p.m. submitter's local time on Tuesday, August 11, 2020.

July 16 | 3:00-4:30pm ET The IUSE: EHR program seeks to promote novel, creative, and transformative approaches to generating and using new knowledge about STEM teaching and learning to improve STEM education for all undergraduates. The program supports proposals interested in improving undergraduate education, developing faculty expertise, preparing K-12 teachers, and providing all undergraduate students with STEM competencies and a basic understanding of STEM concepts and principles. All projects must contribute to the body of knowledge about what works in undergraduate STEM education and the conditions that lead to improved STEM teaching and learning.

Pandemics have far reaching consequences that range from deaths to shutting down the economy as we have witnessed during the recent COVID19 crisis. Hence there is a need to be better prepared for such pandemics. We need to solve problems ranging from predictive analytics innovative devices for saving lives to technology for devising voting machines. The social and economic impact for the above areas is huge and some of the work can be transformative and save lives. Areas of interest to us include, but are not limited to: - Mathematical models for spread and the impact of pandemics. - Scalable simulation techniques for pandemics (e.g. with multi agents). - Biomedical/Nano sensor devices for detecting symptoms and agents. - Algorithms for rapid exploration of the drug screening and discovery workflows (e.g. use reinforcement learning) - Advanced computational biology techniques for sequencing, detecting viral evolution (e.g. in COVID-19). - Algorithms and systems for contact tracing (with privacy preserving). - Algorithms and recommendation systems for curating media and news. - Collaboration techniques for more effective health, and efficiency during pandemics. Improved identity and security techniques. - Distributed Ledgers, their applications and their governance for and during pandemics. - Pandemic data science - understanding the patterns and the impact of a pandemic like COVID-10. Creation of curated data sets. We are interested in both the science and technology aspects of these problem sets, and, particularly, in the intersections between them.

Through the National Center for Education Research (NCER), the Institute of Education Sciences (Institute) provides support for programs of research in areas of demonstrated national need. The Institute's research grant programs are designed to provide interested individuals and the general public with reliable and valid information about education practices that support learning and improve academic achievement and access to education opportunities for all learners. Through the Statistical and Research Methodology in Education grant program, NCER intends to support the development of a wide range of methodological and statistical tools to better enable applied education scientists to conduct rigorous education research.

The worldwide growth of wireless communication, navigation, and telemetry has provided immense societal benefits including mobile broadband data, Internet of Things (IoT), mobile healthcare, and intelligent transportation systems. These and other applications including 5G and beyond wireless systems call for innovations that can circumvent the challenges of radio spectrum scarcity and interference and foster the growth of ubiquitous, high speed, low latency connectivity. Commercial applications like the above must operate in harmony with scientific uses such as research on radio astronomy, Earth and atmospheric sciences, and must not inhibit weather prediction, polar research, and other nationally vital activities, all of which are dependent upon access to the radio spectrum. The National Science Foundation (NSF) continues to support wireless spectrum research and the scientific uses of the electromagnetic spectrum through multiple programs that enable fast, accurate, dynamic coordination and usage of our limited spectrum resource. These programs have created an opportune ground to build and create a large center-based ecosystem for spectrum research, which is the target of this SII-Center program.

The National Science Foundation's Directorates for Engineering (ENG), Computer and Information Science and Engineering (CISE), Mathematical and Physical Sciences (MPS), and Geosciences (GEO) are coordinating efforts to identify new concepts and ideas on Spectrum and Wireless Innovation enabled by Future Technologies (SWIFT). A key aspect of this new solicitation is its focus on effective spectrum utilization and/or coexistence techniques, especially with passive uses, which have received less attention from researchers. Coexistence is when two or more applications use the same frequency band at the same time and/or at the same location, yet do not adversely affect one another. Coexistence is especially difficult when at least one of the spectrum users is passive, i.e., not transmitting any radio frequency (RF) energy. Examples of coexisting systems may include passive and active systems (e.g., radio astronomy and 5G wireless communication systems) or two active systems (e.g., weather radar and Wi-Fi). Breakthrough innovations are sought on both the wireless communication hardware and the algorithmic/protocol fronts through synergistic teamwork. The goal of these research projects may be the creation of new technology or significant enhancements to existing wireless infrastructure, with an aim to benefit society by improving spectrum utilization, beyond mere spectrum efficiency. The SWIFT program seeks to fund collaborative team research that transcends the traditional boundaries of individual disciplines.

The National Science Foundation (NSF) supports fundamental research and education in science and engineering. NSF's role results in new knowledge and tools as well as a capable, innovative workforce. These complementary building blocks of innovation have led to revolutionary technological advances and wholly new industries. NSF seeks to further develop and nurture a national innovation ecosystem built upon fundamental research that guides the output of scientific and engineering discoveries closer to the development of technologies, products, and services that benefit society. The goal of the NSF Innovation Corps (I-Corps) Program is to use experiential education to help entrepreneurial researchers reduce the time necessary to translate a promising idea from the laboratory bench to widespread implementation. In addition to accelerating technology translation, NSF seeks to reduce the risk associated with technology development conducted without insight into industry requirements and challenges.

The Analysis Program supports research in analysis. Areas of current activity include complex, harmonic, and real analysis; dynamical systems and ergodic theory; functional analysis; mathematical physics; operator theory and operator algebras; partial differential equations and calculus of variations.

The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and the Simons Foundation Division of Mathematics and Physical Sciences will jointly sponsor up to two new research collaborations consisting of mathematicians, statisticians, electrical engineers, and theoretical computer scientists. Research activities will be focused on explicit topics involving some of the most challenging questions in the general area of Mathematical and Scientific Foundations of Deep Learning. Each collaboration will conduct training through research involvement of recent doctoral degree recipients, graduate students, and/or undergraduate students from across this multi-disciplinary spectrum. Annual meetings of the Principal Investigators ("PIs") and other principal researchers involved in the collaborations will be held at the Simons Foundation in New York City. This program complements NSF's National Artificial Intelligence Research Institutes program by supporting collaborative research focused on the mathematical and scientific foundations of Deep Learning through a different modality and at a different scale.

The Algorithms for Threat Detection (ATD) program supports research on new ways to use spatiotemporal datasets to develop quantitative models of human dynamics. The objectives include improved representation of complicated group dynamics and the development of algorithms that can process data in near real-time to accurately identify unusual events and forecast future threats indicated by those events.

The National Science Foundation (NSF) through its Divisions of Electrical, Communications and Cyber Systems (ECCS); Chemical, Bioengineering, Environmental and Transport Systems (CBET); Civil, Mechanical and Manufacturing Innovation (CMMI); Information and Intelligent Systems (IIS); and Mathematical Sciences (DMS) announces a solicitation on Multimodal Sensor Systems for Precision Health enabled by Data Harnessing, Artificial Intelligence (AI), and Learning. Next-generation multimodal sensor systems for precision health integrated with AI, machine learning (ML), and mathematical and statistical (MS) methods for learning can be envisioned for harnessing a large volume of diverse data in real time with high accuracy, sensitivity and selectivity, and for building predictive models to enable more precise diagnosis and individualized treatments. It is expected that these multimodal sensor systems will have the potential to identify with high confidence combinations of biomarkers, including kinematic and kinetic indicators associated with specific disease and disability. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts, innovative methodologies, theory, algorithms, and enabling technologies that will address the fundamental scientific issues and technological challenges associated with precision health.

The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and the Simons Foundation Division of Mathematics and Physical Sciences will jointly sponsor up to two new research collaborations consisting of mathematicians, statisticians, electrical engineers, and theoretical computer scientists. Research activities will be focused on explicit topics involving some of the most challenging questions in the general area of Mathematical and Scientific Foundations of Deep Learning. Each collaboration will conduct training through research involvement of recent doctoral degree recipients, graduate students, and/or undergraduate students from across this multi-disciplinary spectrum. Annual meetings of the Principal Investigators ("PIs") and other principal researchers involved in the collaborations will be held at the Simons Foundation in New York City. This program complements NSF's National Artificial Intelligence Research Institutes program by supporting collaborative research focused on the mathematical and scientific foundations of Deep Learning through a different modality and at a different scale.

The Microsoft Foundation is inviting applications for its Dissertation Grants program. The program supports PhD students at North American universities who are underrepresented in the field of computing and pursuing research aligned to the research areas carried out by Microsoft Research. Through the program, recipients will receive funding of up to $25,000 for the 2020-21 academic year as well as an invitation to the PhD Summit, a two-day workshop in the fall held at one of Microsoft Research's labs where fellows will meet with Microsoft researchers and other top students to share their research. Fellows must be aligned in research areas as defined by Microsoft Research, which include artificial intelligence; audio and acoustics; computer vision; graphics and multimedia; human-computer interaction; human language technologies; search and information retrieval; data platforms and analytics; hardware and devices; programming languages and software engineering; security, privacy, and cryptography; systems and networking; algorithms; mathematics; ecology and environment; economics; medical, health, and genomics; social sciences; and technology for emerging markets.