The National Science Foundation has updated and revised their Frequently Asked Questions (FAQ) regarding current and pending support.
The FAQs have been revised alongside the newly developed table, NSF Pre-award and Post-award Disclosures Relating to the Biographical Sketch and Current and Pending Support.
Contact the Policy Office in the Division of Institution and Award Support at policy@nsf.gov with any questions.
The University of Akron’s Office of Research Administration has been informed by the Head of the Policy Office at the National Science Foundation, Jean Feldman, of the following changes:
“We are pleased to announce that a revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 22-1) has been issued.
The new PAPPG will be effective for proposals submitted or due on or after October 4, 2021. Significant changes include:
You are encouraged to review the by-chapter summary of changes provided in the Introduction section of the PAPPG.
NSF plans to conduct a webinar covering these changes. Visit the NSF policy outreach website to sign up for notifications about this and other outreach events.
While this version of the PAPPG becomes effective on October 4, 2021, in the interim, the guidelines contained in the current PAPPG (NSF 20-1) continue to apply.
If you have any questions regarding these changes, please contact the DIAS/Policy Office at policy@nsf.gov.”
The U.S. Department of Justice (DOJ), Office of Justice Programs (OJP), National Institute of Justice (NIJ) is seeking applications for funding innovative doctoral dissertation research that is relevant to preventing and controlling crime, and ensuring the fair and impartial administration of criminal justice in the United States.
This program furthers the Department’s mission by increasing the pool of researchers who are engaged in providing science-based solutions to problems relevant to criminal and juvenile justice policy and practice in the United States. This integrates into a single solicitation for two previously separate fellowship solicitations in Science, Technology, Engineering, and Mathematics (STEM) and Social and Behavior Sciences (SBS). This solicitation incorporates the OJP Grant Application Resource Guide by reference. The OJP Grant Application Resource Guide provides guidance to applicants on how to prepare and submit applications for funding to OJP. If this solicitation expressly modifies any provision in the OJP Grant Application Resource Guide, the applicant is to follow the guidelines in this solicitation as to that provision.
The Graduate Research Fellowship (GRF) program provides grants to accredited academic institutions to support outstanding doctoral students whose dissertation research is relevant to criminal justice. Applicant academic institutions are eligible to apply if the student is currently enrolled in a PhD program and their proposed dissertation research has demonstrable relevance to preventing and controlling crime and/or ensuring the fair and impartial administration of criminal justice in the United States. Awards are anticipated to be made to successful applicant institutions in the form of grants to cover fellowships for the sponsored doctoral students. Awards are made for up to 3 years of support usable over a 5-year period. For each year of support, NIJ provides the institution with $35,000 for Salary and Fringe, up to $12,000 in Cost of Education Allowance, and up to $3,000 in Research Expenses.
The Department of Energy Office of Science (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.
Tools for training AI models on data are readily available and widely used. What is lacking, however, is a theoretical framework for understanding relationships between data and models. For example, given a specific data set and problem, we lack rigorous methods for identifying the best model, hyper-parameters, and training method to use. Given a specific data set and problem, which additional data would be helpful to include in the training set? What information about a dataset can be deduced from a model trained on the data? What attributes of the data can be reverse engineered from a model? What can we learn about model robustness and transfer learning by looking at relationships between data and models?
The primary focus of this FOA topic is to advance our understanding of the relationship between data and models by exploring relationships among them through the development of FAIR frameworks for relating data and models. Such frameworks should provide capabilities that advance our understanding of AI, provide new insights to help researchers with applications of AI techniques, and provide an environment where novel approaches to AI can be explored.
Proposed frameworks may focus on specific disciplines or sub-disciplines currently supported by SC’s programs in ASCR, Biological and Environmental Research (BER), Basic Energy Sciences (BES), Fusion Energy Sciences (FES), High Energy Physics (HEP), Nuclear Physics (NP), or may focus on particular aspects or sub-areas within AI.
The US Military Academy (USMA) at West Point’s mission is “to educate, train, and inspire the Corps of Cadets so that each graduate is a commissioned leader of character committed to the values of Duty, Honor, Country and prepared for a career of professional excellence and service to the Nation as an officer in the United States Army.” USMA executes research to enhance the education of cadets, develop the faculty professionally, and address important issues facing the Army and the Nation. In addition, the Academy conducts research and analysis in emerging fields that may realize novel or vastly improved Army capabilities.
At West Point, research is organized and administered through centers and institutes, most of which reside within academic departments. These centers and institutes, affiliated with each other through the Academy Research Council (ARC), coordinated and supported by the Academic Research Division (ARD), provide the infrastructure necessary to tackle the nation’s and the world’s most challenging problems. Our research centers and institutes bring context to the classroom, are central to our vibrant and pioneering faculty, and are one way West Point connects to the Army and to the Nation. In addition to applied research, there are centers and institutes at West Point that focus on other aspects of the USMA mission.
The USMA BAA identifies topics of interest to the USMA departments, directorates, and research centers and institutes. These groups focus on executing in-house research programs, with a significant emphasis on collaborative research with other organizations. The groups fund a modest amount of extramural research in certain specific areas, and those areas are described in this BAA.
The USMA BAA seeks proposals from institutions of higher education, nonprofit organizations, state and local governments, foreign organizations, foreign public entities, and for-profit organizations (i.e., large and small businesses) for research based on the following campaigns: Socio-Cultural; Information Technology; Ballistics, Weapons, and Protections; Energy and Sustainability; Materials, Measurements, and Facilities; Unmanned Systems and Space; Human Support Systems; and Artificial Intelligence, Machine Learning, and Quantum Technologies.
Proposals are sought for cutting-edge innovative research that could produce discoveries with a significant impact to enable new and improved Army technologies and related operational capabilities and related technologies. The specific research areas and topics of interest described in this document should be viewed as suggestive, rather than limiting.