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MiamiOH OARS

Spectrum and Wireless Innovation enabled by Future Technologies (SWIFT) (nsf20537) | NS... - 0 views

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    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.
MiamiOH OARS

NSF-Simons Research Collaborations on the Mathematical and Scientific Foundations of De... - 0 views

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    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.
MiamiOH OARS

NSF-Simons Research Collaborations on the Mathematical and Scientific Foundations of De... - 0 views

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    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.
MiamiOH OARS

Professional Research Experience Program - 0 views

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    NIST is soliciting applications from eligible institutions of higher education in the U.S. and its territories that offer two- or four- year degrees in academic science, technology, engineering and mathematics (STEM) disciplines, which include but are not limited to biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical sciences, physics, and statistics, to establish and manage a program to support collaborative research relationships among NIST staff, undergraduate and graduate students, individuals with bachelor's or master's degrees, post-doctoral fellows, and academic affiliates, and the PREP researchers' academic institutions. These collaborative relationships will include research opportunities at the relevant NIST campuses in Boulder, Colorado (CO) (PREP Boulder), or Gaithersburg, Maryland (MD), and/or Charleston, South Carolina (SC) (PREP Gaithersburg). Eligible applicants may apply to establish and manage a PREP Boulder program or a PREP Gaithersburg program or may apply to establish and manage programs for both.
MiamiOH OARS

Modeling Infectious Diseases in Healthcare Research Projects to Improve Prevention Rese... - 0 views

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    The purpose of this Notice of Funding Opportunity (NOFO) is to support innovative research to develop and apply computational tools and mathematical methods for: 1) modeling the spread of pathogens that cause healthcare-associated infections (HAIs) and related antimicrobial resistant (AR) infections; 2) predicting outbreaks of HAI pathogens and trends in the burden of antimicrobial resistant and susceptible HAIs; and 3) investigating the effectiveness of intervention strategies. The models should be developed with the intent that they will be tools for researchers, policymakers, or public health workers who want to better understand and respond to HAIs in the United States. This NOFO will also create a network of leaders in the fields of HAI and AR modeling that will be a resource for informing the development of relevant evidence-based policy. MInD-Healthcare will provide a network of leading modelers to respond to evolving public health needs and emergencies in healthcare settings.
MiamiOH OARS

National Academies of Sciences, Engineering, and Medicine Invites Applications for Ford... - 0 views

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    Through its Fellowship Programs, the Ford Foundation seeks to increase the diversity of the nation's college and university faculties by increasing their ethnic and racial diversity, maximize the educational benefits of diversity, and increase the number of professors who can and will use diversity as a resource for enriching the education of all students.
MiamiOH OARS

National Defense Education Program (NDEP) for Science, Technology, Engineering, and Mat... - 0 views

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    The Department of Defense (DoD) seeks innovative applications on mechanisms to implement Science, Technology, Engineering, and Mathematics (STEM) education, outreach, and/or workforce initiative programs, here onto will be referred as STEM activities. The Department intends to award multiple grants, subject to the availability of funds. Each individual award will be up to a maximum of $3,000,000, for a period of up to three (3) years. Applications for larger amounts may be considered on a case-by-case basis.
MiamiOH OARS

Algorithms for Threat Detection (ATD) - 0 views

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    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.
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