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The MCA offers an opportunity for scientists and engineers at the Associate Professor rank (or equivalent) to substantively enhance and advance their research program through synergistic and mutually beneficial partnerships, typically at an institution other than their home institution. Projects that envision new insights on existing problems or identify new but related problems previously inaccessible without new methodology or expertise from other fields are encouraged. Partners from outside the PI's own sub-discipline or discipline are encouraged, but not required, to enhance interdisciplinary networking and convergence across science and engineering fields. By (re)-investing in mid-career investigators, NSF aims to enable and grow a more diverse scientific workforce (more women, persons with disabilities, and underrepresented minorities) at high academic ranks, who remain engaged and active in cutting-edge research.

A key focus of the design of modern computing systems is performance and scalability, particularly in light of the limits of Moore's Law and Dennard scaling. To this end, systems are increasingly being implemented by composing heterogeneous computing components and continually changing memory systems as novel, performant hardware surfaces. Applications fueled by rapid strides in machine learning, data analysis, and extreme-scale simulation are becoming more domain-specific and highly distributed. In this scenario, traditional boundaries between hardware-oriented and software-oriented disciplines increasingly are blurred. Achieving scalability of systems and applications will therefore require coordinated progress in multiple disciplines such as computer architecture, high-performance computing (HPC), programming languages and compilers, security and privacy, systems, theory, and algorithms. Cross-cutting concerns such as performance (including, but not limited to, time, space, and communication resource usage and energy efficiency), correctness and accuracy (including, but not limited to, emerging techniques for program analysis, testing, debugging, probabilistic reasoning and inference, and verification), security and privacy, robustness and reliability, domain-specific design, and heterogeneity must be taken into account from the outset in all aspects of systems and application design and implementation.

Growing Convergence Research (GCR) at the National Science Foundation was identified as one of 10 Big Ideas. Convergence research is a means for solving vexing research problems, in particular, complex problems focusing on societal needs. It entails integrating knowledge, methods, and expertise from different disciplines and forming novel frameworks to catalyze scientific discovery and innovation. GCR identifies Convergence Research as having two primary characteristics: Research driven by a specific and compelling problem. Convergence Research is generally inspired by the need to address a specific challenge or opportunity, whether it arises from deep scientific questions or pressing societal needs. Deep integration across disciplines. As experts from different disciplines pursue common research challenges, their knowledge, theories, methods, data, research communities and languages become increasingly intermingled or integrated. New frameworks, paradigms or even disciplines can form sustained interactions across multiple communities. A distinct characteristic of convergence research, in contrast to other forms of multidisciplinary research, is that from the inception, the convergence paradigm intentionally brings together intellectually diverse researchers and stakeholders to frame the research questions, develop effective ways of communicating across disciplines and sectors, adopt common frameworks for their solution, and, when appropriate, develop a new scientific vocabulary. Research teams practicing convergence aim at developing sustainable relationships that may not only create solutions to the problem that engendered the collaboration, but also develop novel ways of framing related research questions and open new research vistas.

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 U.S. Environmental Protection Agency (EPA), as part of its Science to Achieve Results (STAR) program, is seeking applications proposing research that will address behavioral, technical and practical aspects of interventions and communication strategies to reduce exposures and/or health risks of wildland fire smoke.

NOTE: Webpage provides information about general webinar and BIO Directorate breakout. If you are interested in breakouts for other directorates, contact Heather Johnston (johnsthb@MiamiOH.edu) in Research & Innovation for information. On Wednesday, November 4, 2020 and Thursday, November 5, 2020, NSF will host outreach webinars with information about the Mid-Scale Research Infrastructure (Mid-scale RI)-1 funding opportunity (NSF 21-505). The Mid-scale RI Big Idea is intended to provides an agile, Foundation-wide process to fund experimental research capabilities in the mid-scale range ($6 million to $100 million), between the Major Research Instrumentation (MRI) and Major Facilities thresholds.  Recently, the solicitation (NSF 21-505) for the Mid-scale RI-1 program (for infrastructure with total project cost of $6 million up until, but not including, $20 million) was published with a deadline of January 7, 2021 for preliminary proposals. Each session will begin at 1:00 p.m. EST and have two parts: a general Mid-scale RI-1 information session (1:00 p.m. -1:40 p.m. EST) with Q&A followed by Directorate-specific breakouts (1:45 p.m. - 2:30 p.m. EST) where more technical questions will be addressed. The information presented on Day 1 will be the same as the information presented on Day 2.

This Funding Opportunity Announcement (FOA) intends to accelerate the use of scalable technologies and tools to enhance brain cell census research, including the development of technology platforms and/or resources and the generation of spatiotemporal cell census data and/or resources. Applications are expected to address limitations and gaps of existing technologies/tools as a benchmark against which the improvements or competitive advantages of the proposed ones will be measured. The improvements include throughput, sensitivity, selectivity, scalability, spatiotemporal resolution and reproducibility in cell atlas analyses. The projects funded under this FOA will align with the overarching goals of the BRAIN Initiative Cell Census Network (BICCN) and are expected to enable the generation of a large amount of cell census data using the proposed technologies or via collaboration with the BICCN.

Navigating the New Arctic (NNA) embodies an important forward-looking response by the Foundation to these profound challenges. NNA seeks innovations in fundamental convergence research across the social, natural, environmental, computing and information sciences, and engineering that address the interactions or connections among natural and built environments and social systems, and how these connections inform our understanding of Arctic change and its local and global effects. This solicitation requests proposals that fall within one of three tracks: NNA Planning Grants, dedicated to developing convergence research questions and teams to tackle projects of larger scope in the future; NNA Research Grants, aimed to support creative projects on fundamental research that address convergent scientific and engineering challenges related to the rapidly changing Arctic; and NNA Collaboratory Grants, designed to support collaborative teams undertaking research and training initiatives on critical themes of a broad scope related to the New Arctic.

The RISA program supports the development of knowledge, expertise, and abilities of decision-makers to plan and prepare for climate variability and change. Through regionally-focused and interdisciplinary research and engagement teams, RISA builds and expands the Nation's capacity to adapt and become resilient to extreme weather events and climate change. RISA teams accomplish this through co-developed applied research and partnerships with public and private communities. A central tenet of the RISA program is that learning about climate adaptation and resilience is facilitated by and sustained across a wide range of experts, practitioners, and the public. As such, the RISA program supports a network of people, prioritizing wide participation in learning by doing, learning through adapting, and managing risk with uncertain information. Early decades of the program focused on understanding the use of climate information at regional scales (e.g., through experimental seasonal outlooks), improving predictions and scenarios, building capacity for drought early warning, and advancing the science of climate impact assessments. More recently, emphasis has shifted to address the growing urgency to advance approaches that tackle the complex societal issues surrounding adaptation planning, implementation, and building community resilience. To do so, RISA continues to prioritize collaborative approaches that incorporate multiple knowledge sources and integrate social, physical, and natural science, resulting in long-term support of and increased capacity for communities.

The COVID-19 pandemic has highlighted the need for improved environmental sensing of pathogens. Sensing SARS-CoV-2 virus in the air with high sensitivity and specificity could provide a new mechanism for public health monitoring, enabling safer conditions for a wide range of basic activities including work, travel, and school. SenSARS aims to identify SARS-CoV-2 signatures suitable for rapid indoor air monitoring and use these signatures to develop and demonstrate a technology readiness level (TRL) 4 prototype sensor.

The focus of this BAA is primarily on projects that continue to advance the systems engineering approach needed for the design, fabrication, and manufacture of structural components to address challenges in system weight, performance, affordability, and/or survivability. The foundation of this approach should include the integration of materials information, captured in computational tools, with engineering product performance analysis and manufacturing-process simulation termed commonly as Integrated Computational Materials Engineering (ICME). From this foundation it is expected the integration of manufacturing process information and product performance information utilizing the full range of engineering and analytical tools, processes, and principles to improve efficiency and effectiveness of their integrated approach. The intent is to bring together materials designers, materials suppliers, product designers, and manufacturers to collaborate on the design, production, and commercialization of novel affordable, manufacturable systems. Projects may include basic and applied research, technology and component development, and prototyping; but may also focus on manufacturing supply-chain technical support and integration, workforce development, and manufacturing education.

The Electrical, Communications and Cyber Systems (ECCS) Division supports enabling and transformative research that fuels progress in engineering applications with high societal impacts. ECCS programs encompass novel electronic, photonic, and magnetic devices; communication systems, novel integrated circuits, antennas, sensors; machine learning, control, and networks, to name a few. The fundamental research supported by ECCS impacts a wide range of applications such as communications, energy and power, healthcare, environment, transportation, manufacturing, and other areas. ECCS strongly emphasizes the integration of education into its research programs to support the preparation of a diverse and professionally skilled workforce. ECCS also strengthens its programs through links to other areas of engineering, science, industry, government, and international collaborations. The Addressing Systems Challenges through Engineering Teams (ASCENT) program is a strategic investment of ECCS that emphasizes new collaboration modalities among the various ECCS supported sub-disciplines. ASCENT encourages robust collaborations between the devices, circuits, algorithmic, and network research communities to develop innovative projects. ASCENT seeks proposals that are bold and ground-breaking transcending the perspectives and approaches typical of disciplinary research efforts. ASCENT projects are expected to lead to disruptive technologies or nucleate entirely new research fields motivated by the most pressing societal challenges the global community faces.

DMREF will support activities that significantly accelerate materials discovery and development by building the fundamental knowledge base needed to advance the design and development of materials with desirable properties or functionality. This will be accomplished through forming interdisciplinary teams of researchers working synergistically in a "closed loop" fashion, building a vibrant research community, leveraging data science, providing ready access to materials data, and educating the future MGI workforce. Achieving this goal could involve some combination of: strategies to advance materials design through testing methodology; theory, modeling, and simulation to predict behavior or assist in analysis of multidimensional input data; and validation through synthesis, growth, processing, characterization, and/or device demonstration.

Funds may be used to pay expenses associated with providing technical assistance and/or training (TAT) to: Identify and evaluate solutions to water problems relating to source, storage, treatment, or distribution; identify and evaluate solutions to waste problems relating to collection, treatment, or disposal: assist applicants, that have filed a pre-application with RUS, in the preparation of water and/or waste loan and/or grant applications; and/or provide technical assistance and/or training to water/wastewater system personnel that will improve the management, operation and maintenance of water and waste disposal facilities.

For FY2021, Artificial Intelligence (AI) and Quantum Information Science and Engineering (QISE) have been added to the national priority areas in which the NRT Program encourages proposals. We seek proposals on any interdisciplinary research theme of national priority, with special emphasis on AI and QISE and the six research areas within NSF's 10 Big Ideas. The NSF research Big Ideas are Harnessing the Data Revolution (HDR), The Future of Work at the Human-Technology Frontier (FW-HTF), Navigating the New Arctic (NNA), Windows on the Universe: The Era of Multi-Messenger Astrophysics (WoU), The Quantum Leap: Leading the Next Quantum Revolution (QL), and Understanding the Rules of Life: Predicting Phenotype (URoL). Proposals that align with one of these designated priority areas should contain a title to reflect that alignment, as described in the program solicitation (e.g., NRT-AI: title, NRT-HDR: title, NRT-QL: title). Proposals may be submitted under two tracks (i.e., Track 1 and Track 2). Track 1 proposals may request a total budget (up to five years in duration) up to $3 million for projects with a focus on STEM graduate students in research-based PhD and/or master's degree programs. Track 2 proposals may request a total budget (up to five years in duration) up to $2 million; NSF requires that Track 2 proposals focus on programs from institutions not classified as Doctoral Universities: Very High Research Activity (R1). Requirements for Track 1 and Track 2 are identical.