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On the occasion of its 350th anniversary, Merck KGaA, Darmstadt, Germany will fund innovative projects in applied biophysical & analytical research. Projects will be based on the following challenges: · Challenge 1: Analytical technologies for antibodies and antibody-drug conjugates, as well as technologies to determine drug target engagement, or the level of protein or nucleic acid or metabolic biomarkers. · Challenge 2: Analytical technologies for display materials or semiconductors (Liquid Crystals, OLED Materials, Quantum Materials, Reactive Mesogens, Photoresist Materials). E.g. Spectroscopic Methods, MS Hyphenation, Capillary Chromatography and Comprehensive Separation Technologies; Surface analytics for displays (non- or destructive), Sample preparation techniques for ultra-sensitive investigations · Challenge 3: Analytical technologies for the characterization of polymers, chemical imaging, bioanalytical methods or new methods in molecular biology. Technologies of interest for example are: field flow floractionation (FFF), dynamic light scattering (DLS), chemical imaging, new chromatographic techniques, spectroscopic and spectrometric methods, electron paramagnetic resonance (EPR), microwave analytics

The agency wishes to enter into one or more contracts that prequalifies selected offerors to establish a pool of pre-qualified Contractors that offer public/cloud based analytics platform processing capabilities and to provision for a State Public, Private and Protected data analytics platform suitable for conducting projects very large dataset analysis using a combination of open-source, commercial and vendor proprietary computing and storage platforms including highly complex numerical analysis of textual, structured, non-structured, spatial and other data sources. The agency will also establish a pool of pre-qualified Contractors that are capable of performing Exploratory Projects in a multitude of Data Analytics Domains based upon State agency need.

This Funding Opportunity Announcement (FOA) solicits grant applications proposing exploratory research projects focused on the early-stage development of highly innovative technologies that improve the quality of the samples used for cancer research or clinical care. This includes new capabilities to address issues related to pre-analytical degradation of targeted analytes during the collection, processing, handling, and/or storage of cancer-relevant biospecimens. The overall goal is to support the development of highly innovative technologies capable of maximizing or otherwise interrogating the quality and utility of biological samples used for downstream analyses. This FOA will support the development of tools, devices, instrumentation, and associated methods to preserve or protect sample integrity, or establish verification criteria for quality assessment/quality control and handling under diverse conditions. These technologies are expected to accelerate and/or enhance research in cancer biology, early detection and screening, clinical diagnosis, treatment, epidemiology, or address issues associated with cancer health disparities, by reducing pre-analytical variations that affect biospecimen sample quality.

The NIDCR-funded FaceBase Consortium (www.facebase.org) was established in 2009 to advance craniofacial research by creating comprehensive datasets on craniofacial development and dysmorphologies and disseminating them to the wider craniofacial research community. Operationally, the Consortium links individual spoke projects, each creating and contributing individual datasets, analytic tools, and other resources to a central data management and integration hub which, in turn, disseminates them publicly. This Funding Opportunity Announcement (FOA) solicits grant applications for the role of the FaceBase data management and integration hub. As the Consortiums public face, the hub is charged with the critical functions of collecting datasets and analytic tools developed by the spoke projects, curating and integrating those resources, and disseminating them to the wider research community through the FaceBase website. The hub is expected to work closely with the spoke projects in developing efficient processes for depositing and organizing data, to lead the Consortium in the development of sophisticated methodologies for searching and visualizing integrated FaceBase data, and to coordinate Consortium-wide activities such as working group and Steering Committee meetings, and the annual Consortium-wide meeting.

The focus of this BAA is on discovering and accelerating innovations through three broad technical approaches that contribute to DTRA overarching research, development, technology, and engineering (RDT&E) goals. Analytic investigations; Innovative capability research and development; and Mission-oriented experiments. Projects funded under this BAA will be analytic investigations, capability developments and/or experiments at Technology Readiness Levels (TRL) 2 through 6.

CMMT supports theoretical and computational materials research in the topical areas represented in DMR's Topical Materials Research Programs (these are also variously known as Individual Investigator Award (IIA) Programs, or Core Programs, or Disciplinary Programs), which include: Condensed Matter Physics (CMP), Biomaterials (BMAT), Ceramics (CER), Electronic and Photonic Materials (EPM), Metals and Metallic Nanostructures (MMN), Polymers (POL), and Solid State and Materials Chemistry (SSMC). The CMMT program supports fundamental research that advances conceptual understanding of hard and soft materials, and materials-related phenomena; the development of associated analytical, computational, and data-centric techniques; and predictive materials-specific theory, simulation, and modeling for materials research. First-principles electronic structure, quantum many-body and field theories, statistical mechanics, classical and quantum Monte Carlo, and molecular dynamics, are among the methods used in the broad spectrum of research supported in CMMT. Research may encompass the advance of new paradigms in materials research, including emerging data-centric approaches utilizing data-analytics or machine learning.

This Broad Agency Announcement (BAA) seeks to provide research and development for forming a revolutionary approach to information fusion and analysis by leveraging service-oriented architecture, open standards, and cutting-edge fusion and analytical algorithms to provide real-time (or near real-time) intelligence for decision makers. This BAA shall research and develop novel techniques to assist users with discovering the golden nuggets in the data - potential approaches include fusing diverse data sources, filtering noise, and leveraging pattern learning to derive patterns of life. Further, technical capabilities developed under this BAA will minimize user time spent gathering data and reporting data, while preserving and providing more time for analysis. This will be accomplished through several means to include a data framework that can easily and quickly connect to sundry data sources, a rich, intuitive personalized workspace and experience, a variety of user-defined visualization displays, machine learning to assist and automate mundane tasks, and a custom report generation tool.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) other computing and information researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) other computing and information researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) other computing and information researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) other computing and information researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

Today, complex data-its form, manipulation, and interpretation-are as important to humanities study as more traditional research materials. Datasets, for example, may represent digitized historical records, high-quality image data, or even multimedia collections, all of which are increasing in number due to the availability and affordability of mass data storage devices and international initiatives to create digital content. Moreover, extensive networking capabilities, sophisticated analytical tools, and new collaboration platforms are simultaneously providing and improving interactive access to and analysis of these data as well as a multitude of other resources. The Institutes for Advanced Topics in the Digital Humanities program seeks to enable humanities scholars in the United States to incorporate advances like these into their scholarship and teaching.

Today, complex data-its form, manipulation, and interpretation-are as important to humanities study as more traditional research materials. Datasets, for example, may represent digitized historical records, high-quality image data, or even multimedia collections, all of which are increasing in number due to the availability and affordability of mass data storage devices and international initiatives to create digital content. Moreover, extensive networking capabilities, sophisticated analytical tools, and new collaboration platforms are simultaneously providing and improving interactive access to and analysis of these data as well as a multitude of other resources. The Institutes for Advanced Topics in the Digital Humanities program seeks to enable humanities scholars in the United States to incorporate advances like these into their scholarship and teaching.

The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is sponsoring a Proposers Day to provide information to potential proposers on the objectives of an anticipated Program Solicitation for the SIGMA+ initiative (network and analytics thrust). The Proposers Day will be held on November 9, 2018 from 8:00 AM to 5:00 PM at the Executive Conference Center (4075 Wilson Boulevard, Suite 300, Arlington, VA 22203). The event will be webcast for those who would like to participate remotely. Advance registration is required both for attending the Proposers Day in person and for viewing the webcast. Note, all times listed in this announcement and on the registration website are Eastern Time.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

Hazards SEES seeks research projects that will productively cross the boundaries of the atmospheric and geospace, earth, and ocean sciences; computer and information science; cyberinfrastructure; engineering; mathematics and statistics; and social, economic, and behavioral sciences. Successful proposals will integrate across these multiple disciplines to promote research that advances new paradigms that contribute to creating a society resilient to hazards. Hazards SEES intends to transform hazards and disaster research by fostering the development of interdisciplinary research that allows for appropriately targeted data collection, integration, and management; modeling (including predictive models for real-time decision making); visualization and simulation; data analytics and data-driven discovery; real-time sensing; cross-cutting knowledge development; and synthesis of applicable models and theory. 

Computational approaches play a central role in understanding and advancing sustainability.  CyberSEES supports research on all sustainability topics that depend on advances in computational areas including optimization, modeling, simulation, prediction, and inference; large-scale data management and analytics; advanced sensing techniques; human computer interaction and social computing; infrastructure design, control and management; and intelligent systems and decision-making. Additionally, the widespread, intensive use of computing technologies also introduces sustainability challenges and motivates new approaches across the lifecycle of technology design and use.

The ARI is a joint Domestic Nuclear Detection Office (DNDO) and National Science Foundation (NSF) program seeking novel cross-cutting research that will enhance the nation's ability to detect and interdict nuclear or radiological material outside of regulatory control, and otherwise help prevent nuclear or radiological attacks. This year's solicitation topics will encompass a range of subjects, with an emphasis on unconventional, multidisciplinary approaches to threat detection. A number of small to medium awards are intended in the areas of novel approaches to extremely low-cost threat detection, orthogonal and informatics approaches to threat detection, deterrence analytics, and advanced forensics techniques. A single large award is intended for an integrated, multidisciplinary approach to shielded special nuclear material detection. Primary objectives of the ARI include advancing fundamental knowledge in the above areas and developing intellectual capacity in scientific fields relevant to long-term advances in these areas. Proposals outside of the scope described in this solicitation will be returned without review. Research proposals specific to detection of biological, chemical, and conventional weapons are excluded from the scope of this solicitation, however approaches that consider explosives detection and nuclear or radiological materials detection are of interest.

As part of NSF's Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21) activity, the Directorate for Social, Behavioral, and Economic Sciences (SBE), the Directorate for Education and Human Resources (EHR), and the Office of Cyberinfrastructure seek to enable research communities to develop visions, teams, and capabilities dedicated to creating new, large-scale, next-generation data resources and relevant analytic techniques to advance fundamental research for the SBE and EHR areas of research.  Successful proposals will outline activities that will have significant impacts across multiple fields by enabling new types of data-intensive research.  Investigators should think broadly and create a vision that extends intellectually across multiple disciplines and that includes--but is not limited to--the SBE or EHR areas of research.

MGI recognizes the importance of materials science to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." DMREF integrates materials discovery, development, property optimization, and systems design and optimization, with each employing a toolset to be developed within a materials innovation infrastructure. The toolset will synergistically integrate advanced computational methods and visual analytics with data-enabled scientific discovery and innovative experimental techniques to revolutionize our approach to materials science and engineering.

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.

This program supports theoretical and computational materials research and education in the topical areas represented in DMR programs, including condensed matter physics, polymers, solid-state and materials chemistry, metals and nanostructures, electronic and photonicmaterials, ceramics, and biomaterials. The program supports fundamental research that advances conceptual, analytical, and computational techniques for materials research.

Program supports two main types of research: (i) innovations in general-purpose methodology related to optimization, stochastic modeling, and decision and game theory; and (ii) research grounded in relevant applications that require the development of novel and customized analytical and computational methodologies. Both types of proposals must be motivated by an application area of interest to the program. Application areas of interest include supply chains and logistics; risk management; healthcare; environment; energy production and distribution; mechanism design and incentives; production planning, maintenance, and quality control; and national security