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| data science summer research program: A Moral Political Economy Federica Carugati, Margaret Levi, 2021-06-24 Economies - and the government institutions that support them - reflect a moral and political choice, a choice we can make and remake. Since the dawn of industrialization and democratization in the late eighteenth century, there has been a succession of political economic frameworks, reflecting changes in technology, knowledge, trade, global connections, political power, and the expansion of citizenship. The challenges of today reveal the need for a new moral political economy that recognizes the politics in political economy. It also requires the redesign of our social, economic, and governing institutions based on assumptions about humans as social beings rather than narrow self-serving individualists. This Element makes some progress toward building a new moral political economy by offering both a theory of change and some principles for institutional (re)design. |
| data science summer research program: Data Science for Undergraduates National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-11-11 Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field. |
| data science summer research program: Text as Data Justin Grimmer, Margaret E. Roberts, Brandon M. Stewart, 2022-03-29 A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry |
| data science summer research program: Entering Research Janet L. Branchaw, Amanda R. Butz, Amber Smith, 2019-07-10 For students whose experience with science has been primarily in the classroom, it can be difficult to identify and contact potential mentors, and to navigate the transition to a one-on-one, mentor-student relationship. This is especially true for those who are new to research, or who belong to groups that are underrepresented in research. The Entering Research curriculum offers a mechanism to structure the independent research experience, and help students overcome these challenges. |
| data science summer research program: Law and Policy for the Quantum Age Chris Jay Hoofnagle, Simson L. Garfinkel, 2022-01-06 The Quantum Age cuts through the hype to demystify quantum technologies, their development paths, and the policy issues they raise. |
| data science summer research program: Game Analytics Magy Seif El-Nasr, Anders Drachen, Alessandro Canossa, 2013-03-30 Developing a successful game in today’s market is a challenging endeavor. Thousands of titles are published yearly, all competing for players’ time and attention. Game analytics has emerged in the past few years as one of the main resources for ensuring game quality, maximizing success, understanding player behavior and enhancing the quality of the player experience. It has led to a paradigm shift in the development and design strategies of digital games, bringing data-driven intelligence practices into the fray for informing decision making at operational, tactical and strategic levels. Game Analytics - Maximizing the Value of Player Data is the first book on the topic of game analytics; the process of discovering and communicating patterns in data towards evaluating and driving action, improving performance and solving problems in game development and game research. Written by over 50 international experts from industry and research, it covers a comprehensive range of topics across more than 30 chapters, providing an in-depth discussion of game analytics and its practical applications. Topics covered include monetization strategies, design of telemetry systems, analytics for iterative production, game data mining and big data in game development, spatial analytics, visualization and reporting of analysis, player behavior analysis, quantitative user testing and game user research. This state-of-the-art volume is an essential source of reference for game developers and researchers. Key takeaways include: Thorough introduction to game analytics; covering analytics applied to data on players, processes and performance throughout the game lifecycle. In-depth coverage and advice on setting up analytics systems and developing good practices for integrating analytics in game-development and -management. Contributions by leading researchers and experienced professionals from the industry, including Ubisoft, Sony, EA, Bioware, Square Enix, THQ, Volition, and PlayableGames. Interviews with experienced industry professionals on how they use analytics to create hit games. |
| data science summer research program: Data Science Thinking Longbing Cao, 2018-08-17 This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective. |
| data science summer research program: Public Policy Analytics Ken Steif, 2021-08-18 Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government. |
| data science summer research program: Inorganic Biomaterials Wolfram Höland, Aldo R. Boccaccini, 2016-04-04 Inorganic biomaterials include materials for e.g. dental restorations, biocompatible materials for orthopedic appliances and bioactive materials. However, inorganic biomaterials are also developed for use in tissue regeneration, e.g. wound healing. These products either consist of crystalline phases, such as Al2O3 or ZrO2, which makes them suitable for use in hip bone replacement or they are composed of tricalcium phosphate and used as resorbable biomaterials. Or, they contain glassy phases, such as BIOGLASS®, and are employed as bioactive biomaterials to bond to living bone. Inorganic biomaterials are also used to develop inorganic – organic composites which are suitable for use as bioactive products or to produce dental filling materials. In general, the development of composites is state of the art. However, it is also a future technology. Biomaterials for dental restorations consist of glassy or crystalline phases. Glass-ceramics represent a special group of inorganic biomaterials for dental restorations. Glass-ceramics are composed of at least one inorganic glassy phase and at least one crystalline phase. These products demonstrate a combination of properties, which include excellent aesthetics and the ability to mimic the optical properties of natural teeth, as well as high strength and toughness. They can be processed using special processing procedures, e.g. machining, moulding and sintering, to fabricate high quality products. Sintered oxide ceramics, such as Al2O3 or ZrO2, are also used for the fabrication of dental restorations. These products can be veneered with other biomaterials, or they can be polished to achieve the best possible surface quality. The manuscripts dealing with inorganic biomaterials should focus on the development of the products, especially on their chemical nature, the phase formation processes and all the details related to their processing. Very important are the mechanisms of phase formation. The reader of the manuscript should understand all of these reactions in detail. As far as application is concerned, it is important to describe the main properties of the developed products based on the valid standards, e.g. the ISO standards. The papers published should show that the products comply with these standards. It is very important to understand the relationship between biomass and biomaterials. This will help young scientists to follow the development of biomaterials with new, unexpected properties. He manuscripts published in Frontiers should also focus on the application of the biomaterials. Every manuscript should show the most important application of the material presented. There are different journals that deal with specific product categories, eg Dental Materials. However, Frontiers should allow young scientists to publish their research results using all kinds of inorganic biomaterials. On the other hand, fundamental discussion and analysis of the findings should be encouraged and conclusions about possible applications in the field of medicine and dentistry should be drawn. |
| data science summer research program: The Professor Is In Karen Kelsky, 2015-08-04 The definitive career guide for grad students, adjuncts, post-docs and anyone else eager to get tenure or turn their Ph.D. into their ideal job Each year tens of thousands of students will, after years of hard work and enormous amounts of money, earn their Ph.D. And each year only a small percentage of them will land a job that justifies and rewards their investment. For every comfortably tenured professor or well-paid former academic, there are countless underpaid and overworked adjuncts, and many more who simply give up in frustration. Those who do make it share an important asset that separates them from the pack: they have a plan. They understand exactly what they need to do to set themselves up for success. They know what really moves the needle in academic job searches, how to avoid the all-too-common mistakes that sink so many of their peers, and how to decide when to point their Ph.D. toward other, non-academic options. Karen Kelsky has made it her mission to help readers join the select few who get the most out of their Ph.D. As a former tenured professor and department head who oversaw numerous academic job searches, she knows from experience exactly what gets an academic applicant a job. And as the creator of the popular and widely respected advice site The Professor is In, she has helped countless Ph.D.’s turn themselves into stronger applicants and land their dream careers. Now, for the first time ever, Karen has poured all her best advice into a single handy guide that addresses the most important issues facing any Ph.D., including: -When, where, and what to publish -Writing a foolproof grant application -Cultivating references and crafting the perfect CV -Acing the job talk and campus interview -Avoiding the adjunct trap -Making the leap to nonacademic work, when the time is right The Professor Is In addresses all of these issues, and many more. |
| data science summer research program: Advances in Data Science Ilke Demir, Yifei Lou, Xu Wang, Kathrin Welker, 2021-12-03 This volume highlights recent advances in data science, including image processing and enhancement on large data, shape analysis and geometry processing in 2D/3D, exploration and understanding of neural networks, and extensions to atypical data types such as social and biological signals. The contributions are based on discussions from two workshops under Association for Women in Mathematics (AWM), namely the second Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place between July 29 and August 2, 2019 at the Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, and the third Women in Shape (WiSh) Research Collaboration Workshop that took place between July 16 and 20, 2018 at Trier University in Robert-Schuman-Haus, Trier, Germany. These submissions, seeded by working groups at the conference, form a valuable source for readers who are interested in ideas and methods developed in interdisciplinary research fields. The book features ideas, methods, and tools developed through a broad range of domains, ranging from theoretical analysis on graph neural networks to applications in health science. It also presents original results tackling real-world problems that often involve complex data analysis on large multi-modal data sources. |
| data science summer research program: Big Data and Social Science Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane, 2020-11-17 Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner. |
| data science summer research program: Practical Python Data Wrangling and Data Quality Susan E. McGregor, 2021-12-03 The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Collect data from structured data files, web pages, and APIs Perform basic statistical analyses to make meaning from datasets Visualize and present data in clear and compelling ways |
| data science summer research program: Solar and Space Physics National Research Council, Division on Engineering and Physical Sciences, Space Studies Board, Committee on a Decadal Strategy for Solar and Space Physics (Heliophysics), 2014-09-25 In 2010, NASA and the National Science Foundation asked the National Research Council to assemble a committee of experts to develop an integrated national strategy that would guide agency investments in solar and space physics for the years 2013-2022. That strategy, the result of nearly 2 years of effort by the survey committee, which worked with more than 100 scientists and engineers on eight supporting study panels, is presented in the 2013 publication, Solar and Space Physics: A Science for a Technological Society. This booklet, designed to be accessible to a broader audience of policymakers and the interested public, summarizes the content of that report. |
| data science summer research program: Applications of Machine Learning Prashant Johri, Jitendra Kumar Verma, Sudip Paul, 2020-05-04 This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics. |
| data science summer research program: Mindset Mathematics Jo Boaler, Jen Munson, Cathy Williams, 2017-08-28 Engage students in mathematics using growth mindset techniques The most challenging parts of teaching mathematics are engaging students and helping them understand the connections between mathematics concepts. In this volume, you'll find a collection of low floor, high ceiling tasks that will help you do just that, by looking at the big ideas at the first-grade level through visualization, play, and investigation. During their work with tens of thousands of teachers, authors Jo Boaler, Jen Munson, and Cathy Williams heard the same message—that they want to incorporate more brain science into their math instruction, but they need guidance in the techniques that work best to get across the concepts they needed to teach. So the authors designed Mindset Mathematics around the principle of active student engagement, with tasks that reflect the latest brain science on learning. Open, creative, and visual math tasks have been shown to improve student test scores, and more importantly change their relationship with mathematics and start believing in their own potential. The tasks in Mindset Mathematics reflect the lessons from brain science that: There is no such thing as a math person - anyone can learn mathematics to high levels. Mistakes, struggle and challenge are the most important times for brain growth. Speed is unimportant in mathematics. Mathematics is a visual and beautiful subject, and our brains want to think visually about mathematics. With engaging questions, open-ended tasks, and four-color visuals that will help kids get excited about mathematics, Mindset Mathematics is organized around nine big ideas which emphasize the connections within the Common Core State Standards (CCSS) and can be used with any current curriculum. |
| data science summer research program: Big Data and Social Science Ian Foster, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, Julia Lane, 2016-08-10 Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website. |
| data science summer research program: Data-Driven Security Jay Jacobs, Bob Rudis, 2014-02-24 Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards. |
| data science summer research program: Minority Biomedical Research Support Program , 1993 |
| data science summer research program: Restless Devices Felicia Wu Song, 2021-11-30 We're being formed by our devices. Unpacking the soft tyranny of the digital age, Felicia Wu Song combines insights from psychology, neuroscience, sociology, and theology as she considers digital practices through the lens of liturgy and formation. Exploring pathways of meaningful resistance found in Christian tradition, this resource offers practical experiments for individual and communal change. |
| data science summer research program: Engineering Thermodynamics and 21st Century Energy Problems Donna Riley, 2011-10-28 Energy is a basic human need; technologies for energy conversion and use are fundamental to human survival. As energy technology evolves to meet demands for development and ecological sustainability in the 21st century, engineers need to have up-to-date skills and knowledge to meet the creative challenges posed by current and future energy problems. Further, engineers need to cultivate a commitment to and passion for lifelong learning which will enable us to actively engage new developments in the field. This undergraduate textbook companion seeks to develop these capacities in tomorrow's engineers in order to provide for future energy needs around the world. This book is designed to complement traditional texts in engineering thermodynamics, and thus is organized to accompany explorations of the First and Second Laws, fundamental property relations, and various applications across engineering disciplines. It contains twenty modules targeted toward meeting five often-neglected ABET outcomes: ethics, communication, lifelong learning, social context, and contemporary issues. The modules are based on pedagogies of liberation, used for decades in the humanities and social sciences for instilling critical thinking and reflective action in students by bringing attention to power relations in the classroom and in the world. This book is intended to produce a conversation and creative exploration around how to teach and learn thermodynamics differently. Because liberative pedagogies are at their heart relational, it is important to maintain spaces for discussing classroom practices with these modules, and for sharing ideas for implementing critical pedagogies in engineering contexts. Table of Contents: What and Why? / The First Law: Making Theory Relevant / The Second Law and Property Relations / Thinking Big Picture about Energy and Sustainability |
| data science summer research program: 17th International Conference on Information Technology–New Generations (ITNG 2020) Shahram Latifi, 2020-05-11 This volume presents the 17th International Conference on Information Technology—New Generations (ITNG), and chronicles an annual event on state of the art technologies for digital information and communications. The application of advanced information technology to such domains as astronomy, biology, education, geosciences, security, and healthcare are among the themes explored by the ITNG proceedings. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help information flow to end users are of special interest. Specific topics include Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing. The conference features keynote speakers; a best student contribution award, poster award, and service award; a technical open panel, and workshops/exhibits from industry, government, and academia. |
| data science summer research program: The Grants Register 2024 Palgrave Macmillan, 2023-09-23 The Grants Register 2024 is the most authoritative and comprehensive guide available of postgraduate and professional funding worldwide. It contains international coverage of grants in almost 60 countries, both English and non-English speaking; information on subject areas, level of study, eligibility and value of awards; and information on over 6,000 awards provided by over 1,300 awarding bodies. Awarding bodies are arranged alphabetically with a full list of awards to allow for comprehensive reading. The Register contains full contact details including telephone, fax, email and websites as well as details of application procedures and closing dates. It is updated annually to ensure accurate information. |
| data science summer research program: Sustainable Digital Communities Anneli Sundqvist, Gerd Berget, Jan Nolin, Kjell Ivar Skjerdingstad, 2020-03-19 This volume constitutes the proceedings of the 15th International Conference on Sustainable Digital Communities, iConference 2020, held in Boras, Sweden, in March 2020. The 27 full papers and the 48 short papers presented in this volume were carefully reviewed and selected from 178 submissions. They cover topics such as: sustainable communities; social media; information behavior; information literacy; user experience; inclusion; education; public libraries; archives and records; future of work; open data; scientometrics; AI and machine learning; methodological innovation. |
| data science summer research program: The Science of Reading Margaret J. Snowling, Charles Hulme, 2008-04-15 The Science of Reading: A Handbook brings together state-of-the-art reviews of reading research from leading names in the field, to create a highly authoritative, multidisciplinary overview of contemporary knowledge about reading and related skills. Provides comprehensive coverage of the subject, including theoretical approaches, reading processes, stage models of reading, cross-linguistic studies of reading, reading difficulties, the biology of reading, and reading instruction Divided into seven sections:Word Recognition Processes in Reading; Learning to Read and Spell; Reading Comprehension; Reading in Different Languages; Disorders of Reading and Spelling; Biological Bases of Reading; Teaching Reading Edited by well-respected senior figures in the field |
| data science summer research program: A Mathematician’s Practical Guide to Mentoring Undergraduate Research Michael Dorff, Allison Henrich, Lara Pudwell, 2019-09-16 A Mathematician's Practical Guide to Mentoring Undergraduate Research is a complete how-to manual on starting an undergraduate research program. Readers will find advice on setting appropriate problems, directing student progress, managing group dynamics, obtaining external funding, publishing student results, and a myriad of other relevant issues. The authors have decades of experience and have accumulated knowledge that other mathematicians will find extremely useful. |
| data science summer research program: Scientific and Technical Aerospace Reports , 1995 Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database. |
| data science summer research program: New Developments in Pathways Towards Diversity and Inclusion in STEM: A United States Perspective Alexander Gates, Juan Gilbert, Chris Botanga, Kim Nguyen, Bonita London, 2022-10-17 The Louis Stokes Alliances for Minority Participation (LSAMP) program of the US National Science Foundation has been a primary force for raising the success and graduation of minority students in STEM for 30 years. Increasing the number of underrepresented students earning baccalaureate degrees, and entering graduate school in STEM is the goal of LSAMP. This goal has been nearly achieved through the formation of alliances of degree granting institutions of higher learning, varying from community colleges to major research institutions. Currently there are 59 alliances including more than 400 institutions. LSAMP is responsible for more than 650,000 bachelor’s degrees earned by minority students in STEM. The papers for this Research Topic should focus on the use of LSAMP activities, programs and collaborations to develop pathways to success and graduation of STEM majors from minority groups that underrepresented in STEM. These pathways can include any segment from pre-college through graduate school. Areas of special interest include mentoring, research experiences, transitions between levels and novel approaches for retention. The studies should be research based and rigorous. They can be pure research studies, curriculum and design or literature reviews but they must be at a cutting edge level and be subject to detailed review and assessment. |
| data science summer research program: The Grants Register 2025 Palgrave Macmillan, |
| data science summer research program: The Grants Register 2023 Palgrave Macmillan, 2022-09-28 The Grants Register 2023 is the most authoritative and comprehensive guide available of postgraduate and professional funding worldwide. It contains international coverage of grants in almost 60 countries, both English and non-English speaking; information on subject areas, level of study, eligibility and value of awards; and information on over 6,000 awards provided by over 1,300 awarding bodies. Awarding bodies are arranged alphabetically with a full list of awards to allow for comprehensive reading. The Register contains full contact details including telephone, fax, email and websites as well as details of application procedures and closing dates. It is updated annually to ensure accurate information. |
| data science summer research program: Deep Carbon in Earth: Early Career Scientist Contributions to the Deep Carbon Observatory Donato Giovannelli, Benjamin A. Black, Alysia D. Cox, Cody S. Sheik, 2017-11-27 Since its inception, the Deep Carbon Observatory (DCO) has coalesced a multidisciplinary and international group of researchers focused on understanding and quantifying Earth’s deep carbon budget. Carbon is the fourth most abundant element in the universe, and understanding carbon chemistry under a variety of environmental conditions impacts all aspects of planetary sciences, including planet formation, the form and function of planetary interiors, and the origin and diversity of life. DCO recognizes that is integrating and promoting the contributions of early career scientists are integral to the advancement of knowledge regarding the quantities, movements, origins, and forms of Earth’s deep carbon through field, experimental, analytical, and computational research. Early career scientists represent the future of deep carbon science and contribute substantially to ongoing research by implementing innovative ideas, challenging traditional working schemes, and bringing a globally interconnected perspective to the scientific community. This research topic highlights the contributions at the forefront of deep carbon research by DCO Early Career Scientist community. The manuscripts of this Frontiers e-volume bear evidence of the rapid advances in deep carbon science, and highlights the importance of approaching this field from a plethora of different angles integrating disciplines as diverse as mineralogy, geochemistry and microbiology. This integration is fundamental in understanding the movements and transformations of carbon across its deep cycle. |
| data science summer research program: High Performance Computing Michèle Weiland, Guido Juckeland, Sadaf Alam, Heike Jagode, 2019-12-02 This book constitutes the refereed post-conference proceedings of 13 workshops held at the 34th International ISC High Performance 2019 Conference, in Frankfurt, Germany, in June 2019: HPC I/O in the Data Center (HPC-IODC), Workshop on Performance & Scalability of Storage Systems (WOPSSS), Workshop on Performance & Scalability of Storage Systems (WOPSSS), 13th Workshop on Virtualization in High-Performance Cloud Computing (VHPC '18), 3rd International Workshop on In Situ Visualization: Introduction and Applications, ExaComm: Fourth International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale, International Workshop on OpenPOWER for HPC (IWOPH18), IXPUG Workshop: Many-core Computing on Intel, Processors: Applications, Performance and Best-Practice Solutions, Workshop on Sustainable Ultrascale Computing Systems, Approximate and Transprecision Computing on Emerging Technologies (ATCET), First Workshop on the Convergence of Large Scale Simulation and Artificial Intelligence, 3rd Workshop for Open Source Supercomputing (OpenSuCo), First Workshop on Interactive High-Performance Computing, Workshop on Performance Portable Programming Models for Accelerators (P^3MA). The 48 full papers included in this volume were carefully reviewed and selected. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include HPC computer architecture and hardware; programming models, system software, and applications; solutions for heterogeneity, reliability, power efficiency of systems; virtualization and containerized environments; big data and cloud computing; and artificial intelligence. |
| data science summer research program: Exemplary Science in Grades 9-12 Robert Eugene Yager, 2005 In this collection of 15 essays, educators describe successful programs they've developed to fulfill the US National Science Education Standards' vision for the reform of teaching assessment, professional development, and content at the high school level. All the visions correspond with the Less Emphasis and More Emphasis conditions that conclude each section of the Standards, characterizing what most teachers and programs should do less of as well as describing the changes needed if real reform is to occur. Essay titles reveal the range of programs, and creativity, this book encompasses. Among the titles are: Technology and Cooperative Learning: The IIT Model for Teaching Authentic Chemistry Curriculum, Modeling: Changes in Traditional Physics Instruction, Guided by the Standards: Inquiry and Assessment in Two Rural and Urban Schools, and even Sing and Dance Your Way to Science Success. The book ends with a summary chapter by editor Robert Yager on successes and continuing challenges in meeting the Standards' visions for improving high school science. As Yager notes, The exemplary programs described in this monograph give inspiration while also providing evidence that the new directions are feasible and worth the energy and effort needed for others to implement changes. |
| data science summer research program: Quantitative Social Science Scott, Jacqueline L. Scott, Yu Xie, 2012 |
| data science summer research program: Advancing Educational Outcomes in Science, Technology, Engineering, and Mathematics at Historically Black Colleges and Universities Lamont A. Flowers, Lawrence O. Flowers, James L. Moore III, 2016-10-12 The purpose of this book is to describe critical success factors impacting students pursuing degrees in science, technology, engineering, and mathematics at historically Black colleges and universities. The information in this book is designed to enhance strategies and research to improve students’ engagement experiences, graduation rates, and career development outcomes. |
| data science summer research program: Bulletin , 1986 |
| data science summer research program: The SAGE Handbook of Social Media Research Methods Anabel Quan-Haase, Luke Sloan, 2022-09-02 The SAGE Handbook of Social Media Research Methods spans the entire research process, from data collection to analysis and interpretation. This second edition has been comprehensively updated and expanded, from 39 to 49 chapters. In addition to a new section of chapters focussing on ethics, privacy and the politics of social media data, the new edition provides broader coverage of topics such as: Data sources Scraping and spidering data Locative data, video data and linked data Platform-specific analysis Analytical tools Critical social media analysis Written by leading scholars from across the globe, the chapters provide a mix of theoretical and applied assessments of topics, and include a range of new case studies and data sets that exemplify the methodological approaches. This Handbook is an essential resource for any researcher or postgraduate student embarking on a social media research project. PART 1: Conceptualising and Designing Social Media Research PART 2: Collecting Data PART 3: Qualitative Approaches to Social Media Data PART 4: Quantitative Approaches to Social Media Data PART 5: Diverse Approaches to Social Media Data PART 6: Research & Analytical Tools PART 7: Social Media Platforms PART 8: Privacy, Ethics and Inequalities |
| data science summer research program: A Celebration of the EDGE Program’s Impact on the Mathematics Community and Beyond Susan D'Agostino, Sarah Bryant, Amy Buchmann, Michelle Craddock Guinn, Leona Harris, 2019-08-31 The Enhancing Diversity in Graduate Education (EDGE) Program began twenty years ago to provide support for women entering doctoral programs in the mathematical sciences. With a steadfast commitment to diversity among participants, faculty, and staff, EDGE initially alternated between Bryn Mawr and Spelman Colleges. In later years, EDGE has been hosted on campuses around the nation and expanded to offer support for women throughout their graduate school and professional careers. The refereed papers in A Celebration of the EDGE Program’s Impact on the Mathematics Community and Beyond range from short memoirs, to pedagogical studies, to current mathematics research. All papers are written by former EDGE participants, mentors, instructors, directors, and others connected to EDGE. Together, these papers offer compelling testimony that EDGE has produced a diverse new generation of leaders in the mathematics community. This volume contains technical and non-technical works, and it is intended for a far-reaching audience, including mathematicians, mathematics teachers, diversity officers, university administrators, government employees writing educational or science policy, and mathematics students at the high school, college, and graduate levels. By highlighting the scope of the work done by those supported by EDGE, the volume offers strong evidence of the American Mathematical Society’s recognition that EDGE is a program that makes a difference.” This volume offers unique testimony that a 20-year old summer program has expanded its reach beyond the summer experience to produce a diverse new generation of women leaders, nearly half of whom are underrepresented women. While some books with a women-in-math theme focus only on one topic such as research or work-life balance, this book's broad scope includes papers on mathematics research, teaching, outreach, and career paths. |
| data science summer research program: Systems Engineering and Artificial Intelligence William F. Lawless, Ranjeev Mittu, Donald A. Sofge, Thomas Shortell, Thomas A. McDermott, 2021-11-02 This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges. |
| data science summer research program: Third Symposium Proceedings. New Ways of Teaching and Learning Janina Morska, Alan Rogerson, This volume contains the papers presented at the Third International Symposium on New Ways of Teaching & Learning held from August 6-10, 2024, at the Aemilia Hotel, Bologna, Italy. The Conference was organized by The Mathematics Education for the Future Project - an international educational project founded in 1986 and dedicated to innovation in mathematics, statistics, science and computer education world wide. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with minimum time …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, released in …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process from …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical barriers …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be collected, …
