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Updated annually to include all the vital details of the latest admissions procedures, Getting into Oxford & Cambridge tells you everything you need to know to get onto the course of your choice. With invaluable information and step-by-step guidance, the book will lead you through every step of the process.
Free enterprise is off the leash and is chasing opportunities for profit making across the globe. Challenging the notion of capitalist destiny, this text questions whether capitalism really has brought the levels of economic growth and prosperity that were hoped for.
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.
Updated annually to include all the vital details of the latest admissions procedures, Getting into Medical School takes an honest look at exactly what you need to do to win your place and take the first steps towards your dream career.
This annually updated guide has been helping students stay off the reject pile for over 30 years. With step-by-step guidance on how to fill in your UCAS application, and helpful tip boxes throughout, it provides vital advice on avoiding common mistakes and making your personal statement stand out.
Now in its fifth edition with new and revised content, So you want to go to Oxbridge is the compendium of applying to Oxford and Cambridge, packed full of over eleven years' research on how to excel in the increasingly competitive Oxbridge application process.
This work presents a composite view of medieval English university life. The author offers detailed insights into the social and economic conditions of the lives of students, their teaching masters and fellows. The experiences of college benefactors, women and university servants are also examined, demonstrating the vibrancy they brought to university life. The second half of the book is concerned with the complex methods of teaching and learning, the regime of studies taught, the relationship between the universities in Oxford and Cambridge, as well as the relationship between "town" and "gown".
Building on recent theories of interactive governance and political leadership, Interactive Political Leadership develops a concept of interactive political leadership and a theoretical framework for studying the role of elected politicians in the age of governance. The purpose of the theoretical framework is to inspire and guide empirical research into how elected politicians perform political leadership in a society where citizens and other stakeholders play an active role in making and implementing political decisions and what barriers, challenges, and dilemmas they encounter in relation to the performance of interactive political leadership. The research framework draws extensively on recent theories of interactive governance and political leadership and other new developments in political science and public administration research. Moreover, it finds inspiration in current tendencies and embryonic examples of interactive political leadership performed by elected politicians operating at different levels of governance in Western liberal democracies. The basic assumption is that political legitimacy is essential for the survival of a political system, and that interactive political leadership stands out as a promising way of securing what political scientists denote as input-, throughput-, output-, and outcome legitimacy in the age of governance. Hence, interactive political leadership aims to establish a bridge between representative democracy and emergent forms of political participation, to promote political learning and accountability, to strengthen the political entrepreneurship of elected politicians, and to advance the political system's implementation capacity through resource mobilization. The book develops 20 propositions that sets the agenda for a new and much needed field of empirical research into political leadership in the age of governance.
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.