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The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to develop the appropriate multidisciplinary team, including for example, modelers, bioinformaticians, genomics researchers, social scientists, economists, epidemiologists, entomologists, parasitologists, microbiologists, bacteriologists, virologists, pathologists or veterinarians, with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The Ecology and Evolution of Infectious Diseases program supports research on the ecological, evolutionary, and socio-ecological principles and processes that influence the transmission dynamics of infectious diseases. The central theme of submitted projects must be quantitative or computational understanding of pathogen transmission dynamics. The intent is discovery of principles of infectious disease transmission and testing mathematical or computational models that elucidate infectious disease systems. Projects should be broad, interdisciplinary efforts that go beyond the scope of typical studies. They should focus on the determinants and interactions of transmission among humans, non-human animals, and/or plants. This includes, for example, the spread of pathogens; the influence of environmental factors such as climate; the population dynamics and genetics of reservoir species or hosts; or the cultural, social, behavioral, and economic dimensions of disease transmission. Research may be on zoonotic, environmentally-borne, vector-borne, or enteric diseases of either terrestrial or freshwater systems and organisms, including diseases of animals and plants, at any scale from specific pathogens to inclusive environmental systems. Proposals for research on disease systems of public health concern to developing countries are strongly encouraged, as are disease systems of concern in agricultural systems. Investigators are encouraged to involve the public health research community, including for example, epidemiologists, physicians, veterinarians, food scientists, social scientists, entomologists, pathologists, virologists, or parasitologists with the goal of integrating knowledge across disciplines to enhance our ability to predict and control infectious diseases.

The goals of the Program are to: (i) advance knowledge about the processes that force and regulate the atmosphere’s synoptic and planetary circulation, weather and climate, and (ii) sustain the pool of human resources required for excellence in synoptic and global atmospheric dynamics and climate research.Research topics include theoretical, observational and modeling studies of the general circulation of the stratosphere and troposphere; synoptic scale weather phenomena; processes that govern climate; the causes of climate variability and change; methods to predict climate variations; extended weather and climate predictability; development and testing of parameterization of physical processes; numerical methods for use in large-scale weather and climate models; the assembly and analysis of instrumental and/or modeled weather and climate data; data assimilation studies; development and use of climate models to diagnose and simulate climate and its variations and change.Some Climate and Large Scale Dynamics (CLD) proposals address multidisciplinary problems and are often co-reviewed with other NSF programs, some of which, unlike CLD, use panels in addition to mail reviewers, and thus have target dates or deadlines. Proposed research that spans in substantive ways topics appropriate to programs in other divisions at NSF, e.g., ocean sciences, ecological sciences, hydrological sciences, geography and regional sciences, applied math and statistics, etc., must be submitted at times consistent with target dates or deadlines established by those programs. If it's not clear whether your proposed research is appropriate for co-review, please contact CLD staff (listed above) or the potential co-reviewing program staff (including but not limited to)Eric Itsweire (Physical Oceanography), eitsweir@nsf.govL. Douglas James (Hydrological Sciences), ldjames@nsf.govThomas Baerwald (Geography and Regional Sciences), tbaerwal@nsf.govTom Russell (Applied and Computational Math),

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 goals of the Program are to: (i) advance knowledge about the processes that force and regulate the atmosphere’s synoptic and planetary circulation, weather and climate, and (ii) sustain the pool of human resources required for excellence in synoptic and global atmospheric dynamics and climate research. Research topics include theoretical, observational and modeling studies of the general circulation of the stratosphere and troposphere; synoptic scale weather phenomena; processes that govern climate; the causes of climate variability and change; methods to predict climate variations; extended weather and climate predictability; development and testing of parameterization of physical processes; numerical methods for use in large-scale weather and climate models; the assembly and analysis of instrumental and/or modeled weather and climate data; data assimilation studies; development and use of climate models to diagnose and simulate climate and its variations and change. Some Climate and Large Scale Dynamics (CLD) proposals address multidisciplinary problems and are often co-reviewed with other NSF programs, some of which, unlike CLD, use panels in addition to mail reviewers, and thus have target dates or deadlines. Proposed research that spans in substantive ways topics appropriate to programs in other divisions at NSF, e.g., ocean sciences, ecological sciences, hydrological sciences, geography and regional sciences, applied math and statistics, etc., must be submitted at times consistent with target dates or deadlines established by those programs. If it's not clear whether your proposed research is appropriate for co-review, please contact CLD staff.

The mission of BTO is to foster, demonstrate, and transition breakthrough fundamental research, discoveries, and applications that integrate biology, engineering, computer science, mathematics, and the physical sciences. BTO's investment portfolio goes far beyond life sciences applications in medicine to include areas of research such as human-machine interfaces, microbes as production platforms, and deep exploration of the impact of evolving ecologies and environments on U.S. readiness and capabilities. BTO's programs operate across a wide range of scales, from individual cells to the warfighter to global ecosystems. BTO responds to the urgent and long-term needs of the Department of Defense (DoD) and addresses national security priorities.

The Microsoft Foundation is inviting applications for its Dissertation Grants program. The program supports PhD students at North American universities who are underrepresented in the field of computing and pursuing research aligned to the research areas carried out by Microsoft Research. Through the program, recipients will receive funding of up to $25,000 for the 2020-21 academic year as well as an invitation to the PhD Summit, a two-day workshop in the fall held at one of Microsoft Research's labs where fellows will meet with Microsoft researchers and other top students to share their research. Fellows must be aligned in research areas as defined by Microsoft Research, which include artificial intelligence; audio and acoustics; computer vision; graphics and multimedia; human-computer interaction; human language technologies; search and information retrieval; data platforms and analytics; hardware and devices; programming languages and software engineering; security, privacy, and cryptography; systems and networking; algorithms; mathematics; ecology and environment; economics; medical, health, and genomics; social sciences; and technology for emerging markets.

The Fellowship Program expects to award at least three new Ph.D. Fellowships in 2018 to students who are interested in careers related to marine ecosystem and population dynamics, with a focus on modeling and managing systems of living marine resources. The emphasis will be on the development and implementation of quantitative methods for assessing marine ecosystems, for assessing the status of fish, invertebrate, and other targeted species stocks and for assessing the status of marine mammals, seabirds, and other protected species. Fellows will work on thesis problems of public interest and relevance to National Marine Fisheries Service (NMFS) under the guidance of NMFS mentors at participating NMFS Science Centers or Offices. The NMFS-Sea Grant Fellowship in Population and Ecosystem Dynamics meets NOAA's Healthy Oceans goal of "Marine fisheries, habitats, biodiversity sustained with healthy and productive ecosystems".

The Understanding the Rules of Life: Microbiome Theory and Mechanisms (URoL:MTM) program is an integrative collaborationacross Directorates and Offices within the National Science Foundation. The objective of URoL:MTM is to understand and establish the theory and mechanisms that govern the structure and function of microbiomes, a collection of microbes in a specific habitat/environment. This may include but is not limited to host-associated microbiomes, such as those with humans and other organisms, where i) the microbiome impacts host physiology, behavior, development, and fitness; ii) the host influences the metabolic activity, dynamics and evolution of the microbiome, and iii) the environment (biological, chemical, physical, and social) influences and is influenced by both the host and the microbiome. Recent progress has transformed our ability to identify and catalogue the microbes present in a given environment and measure multiple aspects ofbiological, chemical, physical, and social environments that affect the interactions among the members of the microbiome, the host, and/or habitat. Much descriptive and correlative work has been performed on many microbiome systems, particularly those in the human, soil, aquatic, and built environments. This research has resulted in new hypotheses about the microbiome's contributions to potential system function or dysfunction. The current challenge is to integrate the wide range of accumulated data and information and build on them to develop new causal/mechanistic models or theories of interactions and interdependencies across scales and systems.