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| data science fellows program: ReSearch Teresa M. Evans, Natalie Lundsteen, Nathan L. Vanderford, 2017-05-25 ReSearch: A Career Guide for Scientists is a career planning guide and practical tool for graduate students and postdocs. This book provides step-by-step processes for the assessment of career goals and the actions that can be taken in order to achieve them. ReSearch includes chapters on the basics of career planning, determining unique selling points, and navigating work-life concerns. This book also includes narratives from a number of perspectives to showcase the variety of career options available. ReSearch is written by experts with inside knowledge of how to effectively leverage skills in order to take that next step in your career, whether you are a recent graduate or are interested in transitioning into something new. This book is also a valuable resource for advisors and careers counselors who mentor students and postdocs about their career plans. - Fills the knowledge gap in career planning practices for students and early career researchers in the STEM fields, particularly those in the sciences - Provides global perspectives on seeking career opportunities outside of the United States - Includes strategies for how to market your transferable skill sets, network, and maximize informational interviews - Includes chapters on the basics of career planning, determining unique selling points, and navigating work-life concerns |
| data science fellows program: The Craft of Science Writing Siri Carpenter, 2024-11-05 A deeply sourced, inclusive guide to all aspects of science writing with contributions from some of the most skilled and award-winning authors working today. Science writing has never been so critical to our world, and the demands on writers have never been greater. On any given day, a writer might need to explain the details of AI, analyze developments in climate change research, or serve as a watchdog helping to ensure the integrity of the scientific enterprise. At the same time, writers must spin tales that hook and keep readers, despite the endless other demands on their attention. How does one do it? The Craft of Science Writing is the authoritative guide. With pieces curated from the archives of science writers’ go-to online resource, The Open Notebook, this book explores strategies for finding and shaping story ideas, pitching editors, and building a specialty in science writing. It delves into fundamental skills that every science writer must learn, including planning their reporting; identifying, interviewing, and quoting sources; organizing interview notes; and crafting stories that engage and inform audiences. This expanded edition includes new introductory material and nine new essays focusing on such topics as how to establish a science beat, how to find and use quotes, how to critically evaluate scientific claims, how to use social media for reporting, and how to do data-driven reporting. In addition, there are essays on inclusivity in science writing, offering strategies for eradicating ableist language from stories, working with sensitivity readers, and breaking into English-language media for speakers of other languages. Through interviews with leading journalists offering behind-the-scenes inspiration as well as in-depth essays on the craft offering practical advice, readers will learn how the best science stories get made, from conception to completion. Contributors: Humberto Basilio, Siri Carpenter, Jeanne Erdmann, Dan Ferber, Tina Casagrand Foss, Geoffrey Giller, Laura Helmuth, Jane C. Hu, Alla Katsnelson, Roxanne Khamsi, Betsy Ladyzhets, Jyoti Madhusoodanan, Amanda Mascarelli, Robin Meadows, Kate Morgan, Tiên Nguyễn, Michelle Nijhuis, Aneri Pattani, Rodrigo Pérez Ortega, Mallory Pickett, Kendall Powell, Tasneem Raja, Sandeep Ravindran, Marion Renault, Julia Rosen, Megha Satyanarayana, Christina Selby, Knvul Sheikh, Abdullahi Tsanni, Alexandra Witze, Katherine J. Wu, Wudan Yan, Ed Yong, Rachel Zamzow, Sarah Zhang, and Carl Zimmer |
| data science fellows program: Next Gen PhD Melanie V. Sinche, 2016-08-22 For decades, top scientists in colleges and universities pursued a clear path to success: enroll in a prestigious graduate program, conduct research, publish papers, complete the PhD, pursue postdoctoral work. With perseverance and a bit of luck, a tenure-track professorship awaited at the end. In today’s academic job market, this scenario represents the exception. As the number of newly conferred science PhDs keeps rising, the number of tenured professorships remains stubbornly stagnant. “Next Gen PhD: A Guide to Career Paths in Science is a practical and thorough manual for the entire career transition process, from defining personal interests and deciding on a career path all the way to day one of a new job. Written by experienced career counselor Melanie Sinche, it is geared toward postdocs and graduate students who may not have access to effective career counseling or mentorship or are not satisfied with what they have received thus far.” —Teegan A. Dellibovi-Ragheb, Science “With its focus on PhD level scientists, this book fills a gap in job search and career information literature. It’s a must-read for those contemplating or actively pursuing studies in the subject area, as well as those who provide guidance to undergraduates, graduate students, and postdoctoral scholars.” —Alan Farber, Library Journal (starred review) |
| data science fellows program: Data Driven DJ Patil, Hilary Mason, 2015-01-05 Succeeding with data isn’t just a matter of putting Hadoop in your machine room, or hiring some physicists with crazy math skills. It requires you to develop a data culture that involves people throughout the organization. In this O’Reilly report, DJ Patil and Hilary Mason outline the steps you need to take if your company is to be truly data-driven—including the questions you should ask and the methods you should adopt. You’ll not only learn examples of how Google, LinkedIn, and Facebook use their data, but also how Walmart, UPS, and other organizations took advantage of this resource long before the advent of Big Data. No matter how you approach it, building a data culture is the key to success in the 21st century. You’ll explore: Data scientist skills—and why every company needs a Spock How the benefits of giving company-wide access to data outweigh the costs Why data-driven organizations use the scientific method to explore and solve data problems Key questions to help you develop a research-specific process for tackling important issues What to consider when assembling your data team Developing processes to keep your data team (and company) engaged Choosing technologies that are powerful, support teamwork, and easy to use and learn |
| data science fellows program: Big Data at Work Thomas Davenport, 2014-02-25 Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource. |
| data science fellows program: Improving Equity in Data Science Colby Tofel-Grehl, Emmanuel Schanzer, 2024-06-03 Improving Equity in Data Science offers a comprehensive look at the ways in which data science can be conceptualized and engaged more equitably within the K-16 classroom setting, moving beyond merely broadening participation in educational opportunities. This book makes the case for field wide definitions, literacies and practices for data science teaching and learning that can be commonly discussed and used, and provides examples from research of these practices and literacies in action. Authors share stories and examples of research wherein data science advances equity and empowerment through the critical examination of social, educational, and political topics. In the first half of the book, readers will learn how data science can deliberately be embedded within K-12 spaces to empower students to use it to identify and address inequity. The latter half will focus on equity of access to data science learning opportunities in higher education, with a final synthesis of lessons learned and presentation of a 360-degree framework that links access, curriculum, and pedagogy as multiple facets collectively essential to comprehensive data science equity work. Practitioners and teacher educators will be able to answer the question, “how can data science serve to move equity efforts in computing beyond basic inclusion to empowerment?” whether the goal is to simply improve definitions and approaches to research on data science or support teachers of data science in creating more equitable and inclusive environments within their classrooms. |
| data science fellows program: Analytics and Big Data: The Davenport Collection (6 Items) Thomas H. Davenport, Jeanne G. Harris, 2014-08-12 The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics. |
| data science fellows program: Big Data Is Not a Monolith Cassidy R. Sugimoto, Hamid R. Ekbia, Michael Mattioli, 2016-10-21 Perspectives on the varied challenges posed by big data for health, science, law, commerce, and politics. Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies. The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, “data harm,” and decision making. Contributors Ryan Abbott, Cristina Alaimo, Kent R. Anderson, Mark Andrejevic, Diane E. Bailey, Mike Bailey, Mark Burdon, Fred H. Cate, Jorge L. Contreras, Simon DeDeo, Hamid R. Ekbia, Allison Goodwell, Jannis Kallinikos, Inna Kouper, M. Lynne Markus, Michael Mattioli, Paul Ohm, Scott Peppet, Beth Plale, Jason Portenoy, Julie Rennecker, Katie Shilton, Dan Sholler, Cassidy R. Sugimoto, Isuru Suriarachchi, Jevin D. West |
| data science fellows program: Science & Technology Fellowship Program , |
| data science fellows program: Data Mining Mehmed Kantardzic, 2019-10-21 Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on the topic—explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field. |
| data science fellows program: Data Science in Context Alfred Z. Spector, Peter Norvig, Chris Wiggins, Jeannette M. Wing, 2022-10-20 Four leading experts convey the promise of data science and examine challenges in achieving its benefits and mitigating some harms. |
| data science fellows program: Museums and Digital Culture Tula Giannini, Jonathan P. Bowen, 2019-05-06 This book explores how digital culture is transforming museums in the 21st century. Offering a corpus of new evidence for readers to explore, the authors trace the digital evolution of the museum and that of their audiences, now fully immersed in digital life, from the Internet to home and work. In a world where life in code and digits has redefined human information behavior and dominates daily activity and communication, ubiquitous use of digital tools and technology is radically changing the social contexts and purposes of museum exhibitions and collections, the work of museum professionals and the expectations of visitors, real and virtual. Moving beyond their walls, with local and global communities, museums are evolving into highly dynamic, socially aware and relevant institutions as their connections to the global digital ecosystem are strengthened. As they adopt a visitor-centered model and design visitor experiences, their priorities shift to engage audiences, convey digital collections, and tell stories through exhibitions. This is all part of crafting a dynamic and innovative museum identity of the future, made whole by seamless integration with digital culture, digital thinking, aesthetics, seeing and hearing, where visitors are welcomed participants. The international and interdisciplinary chapter contributors include digital artists, academics, and museum professionals. In themed parts the chapters present varied evidence-based research and case studies on museum theory, philosophy, collections, exhibitions, libraries, digital art and digital future, to bring new insights and perspectives, designed to inspire readers. Enjoy the journey! |
| data science fellows program: Visual Arts , 1988 |
| data science fellows program: Non-Academic Careers for Quantitative Social Scientists Natalie Jackson, 2023-08-14 This book is a guide to non-academic careers for quantitative social scientists. Written by social science PhDs working in large corporations, non-profits, tech startups, and alt-academic positions in higher education, this book consists of more than a dozen chapters on various topics on finding rewarding careers outside the academy. Chapters are organized in three parts. Part I provides an introduction to the types of jobs available to social science PhDs, where those jobs can be found, and what the work looks like in those positions. Part II creates a guide for social science PhDs on how to set themselves up for such careers, including navigating the academic world of graduate school while contemplating non-academic options, and selling their academic experience in a non-academic setting. Part III offers perspectives on timelines for making non-academic career decisions, lifestyle differences between academia and non-academic jobs, and additional resources for those considering a non-academic route. Providing valuable insight on non-academic careers from those who have successfully made the transition, this volume will be an asset to graduate students, advisors, and recent PhDs, in quantitative social science. |
| data science fellows program: So You Want to Be a Neuroscientist? Ashley Juavinett, 2020-12-08 The pursuit to understand the human brain in all its intricacy is a fascinatingly complex challenge and neuroscience is one of the fastest-growing scientific fields worldwide. There is a wide range of career options open to those who wish to pursue a career in neuroscience, yet there are few resources that provide students with inside advice on how to go about it. So You Want to Be a Neuroscientist? is a contemporary and engaging guide for aspiring neuroscientists of diverse backgrounds and interests. Fresh with the experience of having recently launched her own career, Ashley Juavinett provides a candid look at the field, offering practical guidance that explores everything from programming to personal stories. Juavinett begins with a look at the field and its history, exploring our evolving understanding of how the brain works. She then tackles the nitty-gritty: how to apply to a PhD program, the daily life of a graduate student, the art of finding mentors and collaborators, and what to expect when working in a lab. Finally, she introduces readers to diverse young scientists whose career paths illustrate what you can do with a neuroscience degree. For anyone intrigued by the brain or seeking advice on how to further their ambitions of studying it, So You Want to Be a Neuroscientist? is a practical and timely overview of how to learn and thrive in this exciting field. |
| data science fellows program: Digital Transformation Thomas M. Siebel, 2019-07-09 The legendary Silicon Valley entrepreneur examines how both business and government organizations can harness the power of disruptive technologies. Tom Siebel, the billionaire technologist and founder of Siebel Systems, discusses how four technologies—elastic cloud computing, big data, artificial intelligence, and the internet of things—are fundamentally changing how business and government will operate in the 21st century. While this profound and fast-moving transformation can appear daunting to some, Siebel shows how organizations can not only survive, but thrive in the new digital landscape. In this authoritative yet accessible book, Siebel guides readers through the technologies driving digital transformation, and demonstrates how they can strategically exploit their powerful capabilities. He shows how leading enterprises such as Enel, 3M, Royal Dutch Shell, the U.S. Department of Defense, and others are applying AI and IoT with stunning results. |
| data science fellows program: Deep Learning Innovations and Their Convergence With Big Data Karthik, S., Paul, Anand, Karthikeyan, N., 2017-07-13 The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest scholarly research on upcoming trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. Featuring extensive coverage on a broad range of topics and perspectives such as deep neural network, domain adaptation modeling, and threat detection, this book is ideally designed for researchers, professionals, and students seeking current research on the latest trends in the field of deep learning techniques in big data analytics. |
| data science fellows program: Science and Technical Education United States. Congress. House. Committee on Science, Space, and Technology. Subcommittee on Science, Research, and Technology, 1990 |
| data science fellows program: The Grants Register 2025 Palgrave Macmillan, |
| data science fellows 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 fellows program: Leadership in Statistics and Data Science Amanda L. Golbeck, 2021-03-22 This edited collection brings together voices of the strongest thought leaders on diversity, equity and inclusion in the field of statistics and data science, with the goal of encouraging and steering the profession into the regular practice of inclusive and humanistic leadership. It provides futuristic ideas for promoting opportunities for equitable leadership, as well as tested approaches that have already been found to make a difference. It speaks to the challenges and opportunities of leading successful research collaborations and making strong connections within research teams. Curated with a vision that leadership takes a myriad of forms, and that diversity has many dimensions, this volume examines the nuances of leadership within a workplace environment and promotes storytelling and other competencies as critical elements of effective leadership. It makes the case for inclusive and humanistic leadership in statistics and data science, where there often remains a dearth of women and members of certain racial communities among the employees. Titled and non-titled leaders will benefit from the planning, evaluation, and structural tools offered within to contribute inclusive excellence in workplace climate, environment, and culture. |
| data science fellows program: The World According to China Elizabeth C. Economy, 2021-10-25 An economic and military superpower with 20 percent of the world’s population, China has the wherewithal to transform the international system. Xi Jinping’s bold calls for China to “lead in the reform of the global governance system” suggest that he has just such an ambition. But how does he plan to realize it? And what does it mean for the rest of the world? In this compelling book, Elizabeth Economy reveals China’s ambitious new strategy to reclaim the country’s past glory and reshape the geostrategic landscape in dramatic new ways. Xi’s vision is one of Chinese centrality on the global stage, in which the mainland has realized its sovereignty claims over Hong Kong, Taiwan, and the South China Sea, deepened its global political, economic, and security reach through its grand-scale Belt and Road Initiative, and used its leadership in the United Nations and other institutions to align international norms and values, particularly around human rights, with those of China. It is a world radically different from that of today. The international community needs to understand and respond to the great risks, as well as the potential opportunities, of a world rebuilt by China. |
| data science fellows program: Pakistan Under Siege Madiha Afzal, 2018-01-02 Over the last fifteen years, Pakistan has come to be defined exclusively in terms of its struggle with terror. But are ordinary Pakistanis extremists? And what explains how Pakistanis think? Much of the current work on extremism in Pakistan tends to study extremist trends in the country from a detached position—a top-down security perspective, that renders a one-dimensional picture of what is at its heart a complex, richly textured country of 200 million people. In this book, using rigorous analysis of survey data, in-depth interviews in schools and universities in Pakistan, historical narrative reporting, and her own intuitive understanding of the country, Madiha Afzal gives the full picture of Pakistan’s relationship with extremism. The author lays out Pakistanis’ own views on terrorist groups, on jihad, on religious minorities and non-Muslims, on America, and on their place in the world. The views are not radical at first glance, but are riddled with conspiracy theories. Afzal explains how the two pillars that define the Pakistani state—Islam and a paranoia about India—have led to a regressive form of Islamization in Pakistan’s narratives, laws, and curricula. These, in turn, have shaped its citizens’ attitudes. Afzal traces this outlook to Pakistan’s unique and tortured birth. She examines the rhetoric and the strategic actions of three actors in Pakistani politics—the military, the civilian governments, and the Islamist parties—and their relationships with militant groups. She shows how regressive Pakistani laws instituted in the 1980s worsened citizen attitudes and led to vigilante and mob violence. The author also explains that the educational regime has become a vital element in shaping citizens’ thinking. How many years one attends school, whether the school is public, private, or a madrassa, and what curricula is followed all affect Pakistanis’ attitudes about terrorism and the rest of the world. In the end, Afzal suggests how this beleaguered nation—one with seemingly insurmountable problems in governance and education—can change course. |
| data science fellows program: ArcheoFOSS XIV 2020: Open Software, Hardware, Processes, Data and Formats in Archaeological Research Julian Bogdani, Riccardo Montalbano, Paolo Rosati, 2021-12-02 Proceedings of the 14th edition of ArcheoFOSS, 18 high-level and peer reviewed papers are well distributed between two thematic sections—Application Cases and Development, and Open Data—contributed by more than forty Italian and foreign scholars, researchers and freelance archaeologists working in the field of Cultural Heritage. |
| data science fellows program: The Oxford Handbook of the Science of Science Communication Kathleen Hall Jamieson, Dan M. Kahan, Dietram Scheufele, 2017 On topics from genetic engineering and mad cow disease to vaccination and climate change, this Handbook draws on the insights of 57 leading science of science communication scholars who explore what social scientists know about how citizens come to understand and act on what is known by science. |
| data science fellows program: Adoption of Data Analytics in Higher Education Learning and Teaching Dirk Ifenthaler, David Gibson, 2020-08-10 The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education. |
| data science fellows program: State, Foreign Operations, and Related Programs Appropriations for 2017 United States. Congress. House. Committee on Appropriations. Subcommittee on State, Foreign Operations, and Related Programs, 2016 |
| data science fellows program: A Transatlantic History of the Social Sciences Christian Fleck, 2011-02-25 This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. From the beginning of the twentieth century, scientific and social scientific research has been characterised by intellectual exchange between Europe and the US. The establishment of the Third Reich ensured that, from the German speaking world, at least, this became a one-way traffic. In this book Christian Fleck explores the invention of empirical social research, which by 1950 had become the binding norm of international scholarship, and he analyses the contribution of German refugee social scientists to its establishment. The major names are here, from Adorno and Horkheimer to Hirshman and Lazarsfeld, but at the heart of the book is a unique collective biography based on original data from more than 800 German-speaking social scientists. Published in German in 2008 to great acclaim, Fleck's important study of the transatlantic enrichment of the social sciences is now available in a revised English-language edition. |
| data science fellows program: Bulletin of the Atomic Scientists , 1977-11 The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic Doomsday Clock stimulates solutions for a safer world. |
| data science fellows 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 fellows program: Atomic Energy Commission Fellowship Program United States. Congress. Joint Committee on Atomic Energy, 1949 |
| data science fellows program: A Patron for Pure Science James Merton England, 1982 |
| data science fellows program: Federal Scholarship and Fellowship Programs and Other Government Aids to Students, a Report Prepared in the Legislative Reference Service of the Library of Congress ..... 1950 United States. Congress. House. Committee on Education and Labor, 1950 |
| data science fellows program: Redesigning Liberal Education William Moner, Phillip Motley, Rebecca Pope-Ruark, 2020-07-07 Redesigning liberal education requires both pragmatic approaches to discover what works and radical visions of what is possible. The future of liberal education in the United States, in its current form, is fraught but full of possibility. Today's institutions are struggling to maintain viability, sustain revenue, and assert value in the face of rising costs. But we should not abandon the model of pragmatic liberal learning that has made America's colleges and universities the envy of the world. Instead, Redesigning Liberal Education argues, we owe it to students to reform liberal education in ways that put broad and measurable student learning as the highest priority. Written by experts in higher education, the book is organized into two sections. The first section focuses on innovations at 13 institutions: Brown University, College of the Holy Cross, Connecticut College, Elon University, Florida International University, George Mason University, Georgetown University, Lasell College, Northeastern University, Rollins College, Smith College, Susquehanna University, and the University of Wisconsin–Green Bay. Chapters about these institutions consider the vast spectrum of opportunities and challenges currently faced by students, faculty, staff, and administrators, while also offering radical visions of the future of liberal education in the United States. Accompanying vision chapters written by some of the foremost leaders in higher education touch on a wide array of subjects and themes, from artificial intelligence and machines to the role that human dispositions, mindsets, resilience, and time play in how we guide students to ideas for bringing playful concepts of creativity and openness into our work. Ultimately, Redesigning Liberal Education reveals how humanizing forces, including critical thinking, collaboration, cross-cultural competencies, resilience, and empathy, can help drive our world. This uplifting collection is a celebration of the innovative work being done to achieve the promise of a valuable, engaging, and practical undergraduate liberal education. Isis Artze-Vega, Denise S. Bartell, Randy Bass, John Bodinger de Uriarte, Laurie Ann Britt-Smith, Jacquelyn Dively Brown, Phillip M. Carter, Nancy L. Chick, Michael J. Daley, Maggie Debelius, Janelle Papay Decato, Peter Felten, Ashley Finley, Dennis A. Frey Jr., Chris W. Gallagher, Evan A. Gatti, Lisa Gring-Pemble, Kristína Moss Gudrún Gunnarsdóttir, Anthony Hatcher, Toni Strollo Holbrook, Derek Lackaff, Leo Lambert, Kristin Lange, Sherry Lee Linkon, Anne M. Magro, Maud S. Mandel, Jessica Metzler, Borjana Mikic, William Moner, Phillip Motley, Matthew Pavesich, Uta G. Poiger, Rebecca Pope-Ruark, Michael Reder, Michael S. Roth, Emily Russell, Heather Russell, Ann Schenk, Michael Shanks, Susan Rundell Singer, Andrea A. Sinn, Christina Smith, Allison K. Staudinger, William M. Sullivan, Connie Svabo, Meredith Twombly, Betsy Verhoeven, David J. Voelker, Scott Windham, Mary C. Wright, Catherine Zeek |
| data science fellows program: Drawdown Paul Hawken, 2017-04-18 • New York Times bestseller • The 100 most substantive solutions to reverse global warming, based on meticulous research by leading scientists and policymakers around the world “At this point in time, the Drawdown book is exactly what is needed; a credible, conservative solution-by-solution narrative that we can do it. Reading it is an effective inoculation against the widespread perception of doom that humanity cannot and will not solve the climate crisis. Reported by-effects include increased determination and a sense of grounded hope.” —Per Espen Stoknes, Author, What We Think About When We Try Not To Think About Global Warming “There’s been no real way for ordinary people to get an understanding of what they can do and what impact it can have. There remains no single, comprehensive, reliable compendium of carbon-reduction solutions across sectors. At least until now. . . . The public is hungry for this kind of practical wisdom.” —David Roberts, Vox “This is the ideal environmental sciences textbook—only it is too interesting and inspiring to be called a textbook.” —Peter Kareiva, Director of the Institute of the Environment and Sustainability, UCLA In the face of widespread fear and apathy, an international coalition of researchers, professionals, and scientists have come together to offer a set of realistic and bold solutions to climate change. One hundred techniques and practices are described here—some are well known; some you may have never heard of. They range from clean energy to educating girls in lower-income countries to land use practices that pull carbon out of the air. The solutions exist, are economically viable, and communities throughout the world are currently enacting them with skill and determination. If deployed collectively on a global scale over the next thirty years, they represent a credible path forward, not just to slow the earth’s warming but to reach drawdown, that point in time when greenhouse gases in the atmosphere peak and begin to decline. These measures promise cascading benefits to human health, security, prosperity, and well-being—giving us every reason to see this planetary crisis as an opportunity to create a just and livable world. |
| data science fellows program: 1994 NASA Authorization United States. Congress. House. Committee on Science, Space, and Technology. Subcommittee on Technology, Environment, and Aviation, 1993 |
| data science fellows program: International Science in the National Interest at the U.S. Geological Survey National Research Council, Division on Earth and Life Studies, Board on Earth Sciences and Resources, Committee on Opportunities and Challenges for International Science at the U.S. Geological Survey, 2012-08-18 Science at the U.S. Geological Survey (USGS) is intrinsically global, and from early in its history, the USGS has successfully carried out international projects that serve U.S. national interests and benefit the USGS domestic mission. Opportunities abound for the USGS to strategically pursue international science in the next 5-10 years that bears on growing worldwide problems having direct impact on the United States-climate and ecosystem changes, natural disasters, the spread of invasive species, and diminishing natural resources, to name a few. Taking a more coherent, proactive agency approach to international science-and building support for international projects currently in progress-would help the USGS participate in international science activities more effectively. |
| data science fellows program: Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI Jeffrey Nichols, Becky Verastegui, Arthur ‘Barney’ Maccabe, Oscar Hernandez, Suzanne Parete-Koon, Theresa Ahearn, 2020-12-22 This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020. The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; system software: data infrastructure and life cycle; experimental/observational applications: use cases that drive requirements for AI and HPC convergence; deploying computation: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic. |
| data science fellows program: Catalog of Federal Domestic Assistance United States. Office of Management and Budget, 2009 Identifies and describes specific government assistance opportunities such as loans, grants, counseling, and procurement contracts available under many agencies and programs. |
| data science fellows program: International Cooperation in Science United States. Congress. House. Committee on Science and Technology. Task Force on Science Policy, 1985 |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
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Insight Data Science Fellows Program Cost
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CARES Act Two Year Fact Sheet - Pandemic Oversight
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U.S. Army Cyber Command (ARCYBER) Career Exploration, …
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PRAC Data Fellow PD - Pandemic Oversight
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Insight Data Science Fellows Program Cost (2024)
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The Data Drip
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Science Leadership Program - Manager
Our Science Leadership Program (SLP) is how Schmidt Science Fellows, working across the world, come together in fellowship to build the skills, experience, and ... analyze quantitative …
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EMERGING TECHNOLOGIES COMMITTEE
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Sacramento Kings Startup Competition Two UC Davis …
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SCAG’s Future Communities Initiative
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AIM-AHEAD CLINAQ Fellows Program Cohort 2 Webinar
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2024 Vacancy Announcement for U.S. Army Fellow - CYBERCOM
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2023-24 Sheridan Center for Teaching and Learning Annual …
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stephen.k.bailey@vanderbilt.edu Interdisciplinary Data …
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Wim Van Criekinge, An Explosion of Bioinformatics Careers
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concerning - United States Department of Justice Office of the ...
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CMU Rales Fellows Fact Sheet
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