Mathematical analysis is at the nexus of contemporary mathematics and its applications. It is the branch of mathematics most directly connected to the activity of describing aspects of the world in quantitative terms. Problems originating in science, engineering and industry typically reach mathematics by way of analysis, while new mathematical ideas, methodologies, techniques and algorithms, more often than not, enter application areas through analysis. Thus, the health of analysis, which provides the conceptual framework and technology and thereby underpins the majority of novel applications of mathematics in science, engineering and industry, and the provision of quality personnel in this subject are of key importance not just to the future of UK mathematics but to the UK science base in its entirety, indeed to the government strategy in fostering economic growth through scientific development and innovation.There is a critical need for knowledge transfer from specialized expert mathematical communities in analysis (partial differential equations, harmonic analysis, stochastic analysis) into the applied modelling community. This knowledge transfer is presently a recognized UK weakness. We believe that the reverse transfer, by which work on mathematical fundamentals is stimulated and focussed by modelling challenges in applications, is also a vital ingredient of a healthy mathematical community. Cambridge analysis is not confined to one specialized area but includes internationally strong individuals and groups in PDEs for mathematical physics, applications of PDEs, stochastic analysis, computational analysis, together with an unrivalled tradition in applied mathematical modelling. The ongoing realignment and interconnection of these groups gives an excellent environment in which to establish a Centre for Doctoral Training in analysis, which will enable doctoral students to experience the power and excitement of the mathematical modelling process from beginning to end, that is, from a physical, biological or industrial problem not yet formulated in mathematical terms, to a mathematical model, understood by rigorous theory and efficient computation, and then to see the results used for effective prediction, control or scientific understanding.The CDT will offer an enhanced graduate programme in pure and applied analysis. The aim is to create a distinctive team of young analysts who see the scope of their work as ranging from leading-edge theory to leading-edge applications. This is difficult within the standard three-year PhD framework. Through an initial period of richer training integrated with wider research experience, allowed by the CDT, students will develop a mixture of pure, stochastic, applied and computational skills, which will be a highly effective preparation for the specialized research required for a PhD. Continuing training activities throughout the duration of the CDT programme will encourage breadth of interest and approach. The CDT will engage with the Cambridge research environment, both within the University and outside in the research institutes and other enterprises which form the Cambridge phenomenon, building on existing links, to make a strong connection between the leading edge of core analysis and diverse and important applications areas.
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