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The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II).  Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering.  Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies.  Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.

The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II). Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering. Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies. Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.

Future ultra-low-energy computing, storage and signal-processing systems can be built on principles derived from organic systems that are at the intersection of chemistry, biology, and engineering. New information technologies can be envisioned that are based on biological principles and that use biomaterials in the fabrication of devices and components; it is anticipated that these information technologies could enable stored data to be retained for more than 100 years and storage capacity to be 1,000 times greater than current capabilities. These could also facilitate compact computers that will operate with substantially lower power than today's computers. Research in support of these goals can have a significant impact on advanced information processing and storage technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, engineering, physics, chemistry, materials science, computer science, and information science that will enable heretofore-unanticipated breakthroughs as well as meet educational goals.

The NIGMS Postdoctoral Research Associate (PRAT) Programs overarching goal is to provide high quality postdoctoral research training in the basic biomedical sciences, in NIH intramural research laboratories, to a diverse group of postdoctoral fellows to prepare them for leadership positions in biomedical careers. The research projects proposed should focus on NIGMS mission-related areas of basic biomedical science. These include cell biology, biophysics, genetics, developmental biology, pharmacology, physiology, biological chemistry, computational biology, technology development and bioinformatics. Studies employing model organisms are encouraged

This FOA invites applications for the Microphysiological Systems (MPS) for Disease Modeling and Efficacy Testing Program to develop highly reproducible and translatable in vitro models for preclinical efficacy studies through discovery and validation of translatable biomarkers, development of standardized methods for preclinical efficacy testing and definitive efficacy testing of candidate therapeutics using best practices and rigorous study design. An essential feature will be a multidisciplinary approach that brings together experts in bioengineering, microfluidics, material science, "omic" sciences, computational biology, disease biology, pathology, electrophysiology, pharmacology, biostatistics and clinical science.

This FOA invites applications for the Microphysiological Systems (MPS) for Disease Modeling and Efficacy Testing Program to develop highly reproducible and translatable in vitro models for preclinical efficacy studies through discovery and validation of translatable biomarkers, development of standardized methods for preclinical efficacy testing and definitive efficacy testing of candidate therapeutics using best practices and rigorous study design. An essential feature will be a multidisciplinary approach that brings together experts in bioengineering, microfluidics, material science, "omic" sciences, computational biology, disease biology, pathology, electrophysiology, pharmacology, biostatistics and clinical science.

Scientific advances such as genomics, quantitative structural biology, imaging techniques, and modeling of complex systems have created opportunities for exciting research careers at the interface between the physical/computational sciences and the biological sciences. Tackling key problems in biology will require scientists trained in areas such as chemistry, physics, applied mathematics, computer science, and engineering. Recognizing the vital role such cross-trained scientists will play in furthering biomedical science, the Burroughs Wellcome Fund has developed the Career Awards at the Scientific Interface. These grants are intended to foster the early career development of researchers who have transitioned or are transitioning from undergraduate and/or graduate work in the physical/mathematical/computational sciences or engineering into postdoctoral work in the biological sciences, and who are dedicated to pursuing a career in academic research. Candidates are expected to draw from their training in a scientific field other than biology to propose innovative approaches to answer important questions in the biological sciences.

New information technologies can be envisioned that are based on biological principles and that use biomaterials in the fabrication of devices and components; it is anticipated that these information technologies could enable stored data to be retained for more than 100 years and storage capacity to be 1,000 times greater than current capabilities. These could also facilitate compact computers that will operate with substantially lower power than today's computers. Research in support of these goals can have a significant impact on advanced information processing and storage technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, engineering, physics, chemistry, materials science, computer science, and information science that will enable heretofore-unanticipated breakthroughs as well as meet educational goals.

The Division of Environmental Biology (DEB) supports fundamental research on populations, species, communities, and ecosystems. Scientific emphases range across many evolutionary and ecological patterns and processes at all spatial and temporal scales. Areas of research include biodiversity, phylogenetic systematics, molecular evolution, life history evolution, natural selection, ecology, biogeography, ecosystem structure, function and services, conservation biology, global change, and biogeochemical cycles. Research on organismal origins, functions, relationships, interactions, and evolutionary history may incorporate field, laboratory, or collection-based approaches; observational or manipulative experiments; synthesis activities; as well as theoretical approaches involving analytical, statistical, or computational modeling.

The Mathematical Biology Program supports research in areas of applied and computationalmathematics with relevance to the biological sciences. Successful proposals are mathematically innovative and address challenging problems of interest to members of the biological community. Some projects of interest to the Mathematical Biology Program may include development of mathematical concepts and tools traditionally seen in other disciplinary programs within the Division of Mathematical Sciences, e.g., topology, probability, statistics, computational mathematics, etc. To receive appropriate and timely review, such proposals should be submitted directly to the relevant disciplinary program that has the earliest deadline, with other program(s) selected as secondary. Note that proposals that use established mathematical and computational tools to address problems in the biological sciences are typically not appropriate for submission to DMS. For further details on other disciplinary programs within DMS, see the corresponding program descriptions. In general, if a proposal is appropriate for review by more than one NSF program, it is advisable to contact the program officers handling each program to determine when the proposal should be submitted and to facilitate the review process.

The mission of BTO is to leverage biology as a technology to solve intractable problems. BTO seeks to leverage advances in engineering and computer science to drive and reshape biotechnology for national security. To achieve this vision, BTO is interested in a range of emerging technical areas, including but not limited to human-machine interfaces, human performance, infectious disease, and synthetic biology. The overarching goal is to develop, demonstrate, and transition biologically-based technologies as part of the national security toolkit.

Candidates must hold a Ph.D. (or equivalent) in chemistry, computational or evolutionary molecular biology, computer science, economics, mathematics, neuroscience, ocean sciences (including marine biology), physics, or a related field; Candidates must hold a tenure track (or equivalent) position at a college, university or other degree-granting institution in the United States or Canada;  Candidates must normally be no more than six years from completion of their most recent Ph.D. (or equivalent) as of the year of their nomination.  (That is, most recent Ph.D. must have been awarded on or after September 2007.)** While Fellows are expected to be at an early stage of their research careers, there should be strong evidence of independent research accomplishments. Candidates in all fields are normally below the rank of associate professor and do not hold tenure, but these are not strict requirements. The Alfred P. Sloan Foundation welcomes nominations of all candidates who meet the traditional high standards of this program, and strongly encourages the participation of women and members of underrepresented minority groups.

The Cellular and Biochemical Engineering (CBE)program is part of the Engineering Biology and Health cluster, which also includes 1) Biophotonics; 2) Biosensing; 3) Disability and Rehabilitation Engineering; and 4) Engineering of Biomedical Systems. TheCellular and Biochemical Engineering program supports fundamental engineering research that advances understanding of cellular andbiomolecular processes in engineering biology. CBE-funded research eventually leads to the development of enabling technology for advanced biomanufacturing in support of the therapeutic cell, biochemical, biopharmaceutical, and biotechnology industries. Fundamental to many research projects in this area is the understanding of how biomolecules, subcellular systems, cells, and cell populations interact in the biomanufacturing environment, and how those interactions lead to changes in structure, function, and behavior. A quantitative treatment of problems related to biological processes is considered vital to successful research projects in the CBE program. The program encourages highly innovative and potentially transformative engineering research leading to novel bioprocessing and biomanufacturing approaches. The CBE program also encourages proposals that effectively integrate knowledge and practices from different disciplines while incorporating ongoing research into educational activities.

The Law & Science Program considers proposals that address social scientific studies of law and law-like systems of rules, as well as studies of how science and technology are applied in legal contexts. The Program is inherently interdisciplinary and multi-methodological. Successful proposals describe research that advances scientific theory and understanding of the connections between human behavior and law, legal institutions, or legal processes; or the interactions of law and basic sciences, including biology, computer and information sciences, STEM education, engineering, geosciences, and math and physical sciences. Scientific studies of law often approach law as dynamic, interacting with multiple arenas, and with the participation of multiple actors. Fields of study include many disciplines, and often address problems including, though not limited, to: Crime, Violence, and Policing Cyberspace Economic Issues Environmental Science Evidentiary Issues Forensic Science Governance and Courts Human Rights and Comparative Law Information Technology Legal and Ethical Issues related to Science Legal Decision Making Legal Mobilization and Conceptions of Justice Litigation and the Legal Profession Punishment and Corrections Regulation and Facilitation of Biotechnology (e.g., Gene Editing, Gene Testing, Synthetic Biology) and Other Emerging Sciences and Technologies Use of Science in the Legal Processes

The goal of the Biophotonics program is to explore the research frontiers in photonics principles, engineering and technology that are relevant for critical problems in fields of medicine, biology and biotechnology.  Fundamental engineering research and innovation in photonics is required to lay the foundations for new technologies beyond those that are mature and ready for application in medical diagnostics and therapies.  Advances are needed in nanophotonics, optogenetics, contrast and targeting agents, ultra-thin probes, wide field imaging, and rapid biomarker screening. Low cost and minimally invasive medical diagnostics and therapies are key motivating application goals.

The goal of the Biophotonics program is to explore the research frontiers in photonics principles, engineering and technology that are relevant for critical problems in fields of medicine, biology and biotechnology.  Fundamental engineering research and innovation in photonics is required to lay the foundations for new technologies beyond those that are mature and ready for application in medical diagnostics and therapies.  Advances are needed in nanophotonics, optogenetics, contrast and targeting agents, ultra-thin probes, wide field imaging, and rapid biomarker screening. Low cost and minimally invasive medical diagnostics and therapies are key motivating application goals.

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science

The SD2 program aims to develop data-driven methods to accelerate scientific discovery and robust design in domains that lack complete models. Engineers regularly use high-fidelity simulations to create robust designs in complex domains such as aeronautics, automobiles, and integrated circuits. In contrast, robust design remains elusive in domains such as synthetic biology, neuro-computation, cyber, and polymer chemistry due to the lack of high-fidelity models. SD2 will develop tools to enable robust design despite the lack of complete scientific models.

Our Data-Driven Discovery Initiative seeks to advance the people and practices of data-intensive science, to take advantage of the increasing volume, velocity, and variety of scientific data to make new discoveries. Within this initiative, we're supporting data-driven discovery investigators - individuals who exemplify multidisciplinary, data-driven science, coalescing natural sciences with methods from statistics and computer science. These innovators are striking out in new directions and are willing to take risks with the potential of huge payoffs in some aspect of data-intensive science. Successful applicants must make a strong case for developments in the natural sciences (biology, physics, astronomy, etc.) or science enabling methodologies (statistics, machine learning, scalable algorithms, etc.), and applicants that credibly combine the two are especially encouraged. Note that the Science Program does not fund disease targeted research. It is anticipated that the DDD initiative will make about 15 awards at ~$1,500,000 each, at $200K-$300K/year for five years.

Pathway supports innovative basic, clinical, translational, epidemiological, behavioral, or health services research relevant to any diabetes type, diabetes-related disease state, or diabetes complication. The Association seeks exceptional candidates from a broad range of disciplines, including medicine, biology, chemistry, computing, physics, mathematics and engineering.

The Division of Molecular and Cellular Biosciences (MCB) supports quantitative, predictive, and theory-driven fundamental research and related activities designed to promote understanding of complex living systems at the molecular, subcellular, and cellular levels. MCB is soliciting proposals for hypothesis-driven and discovery research and related activities in four core clusters: Molecular Biophysics Cellular Dynamics and Function Genetic Mechanisms Systems and Synthetic Biology MCB gives high priority to research projects that use theory, methods, and technologies from physical sciences, mathematics, computational sciences, and engineering to address major biological questions.  Research supported by MCB uses a range of experimental approaches--including in vivo, in vitro and in silico strategies--and a broad spectrum of model and non-model organisms, especially microbes and plants. Typical research supported by MCB integrates theory and experimentation.  Projects that address the emerging areas of multi-scale integration, molecular and cellular evolution, quantitative prediction of phenome from genomic information, and development of methods and resources are particularly welcome.

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science. The solicitation invites two types of proposals: "Foundations" (F): those developing or studying fundamental theories, techniques, methodologies, technologies of broad applicability to Big Data problems; and "Innovative Applications" (IA): those developing techniques, methodologies and technologies of key importance to a Big Data problem directly impacting at least one specific application. Therefore, projects in this category must be collaborative, involving researchers from domain disciplines and one or more methodological disciplines, e.g., computer science, statistics, mathematics, simulation and modeling, etc. While Innovative Applications (IA) proposals may address critical big data challenges within a specific domain, a high level of innovation is expected in all proposals and proposals should, in general, strive to provide solutions with potential for a broader impact on data science and its applications. IA proposals may focus on novel theoretical analysis and/or on experimental evaluation of techniques and methodologies within a specific domain. Proposals in all areas of sciences and engineering covered by participating directorates at NSF are welcome.