EPSRC and MRC Centre for Doctoral Training in Mathematics for Real-World Systems

MathSys涉及EPSRC在数学科学方面的CDT优先领域中的两个：“高度连接的真实世界系统的数学”和“生物学和医学中的新数学”。我们将培训下一代熟练的应用数学研究人员使用和开发尖端技术，使他们能够应对科学、工业和现代社会面临的一系列挑战。我们的博士培训中心将建立在华威复杂性科学DTC的经验和成功的基础上，同时完善所解决问题的范围。它将为学生提供一个支持性和激励性的环境，在这个环境中，可以解决支持不同学科问题的常见数学挑战。对在跨学科环境中接受培训的具有数学技能的研究人员的需求从未像现在这样强烈，这被视为行业和政府的主要障碍。报告和商界领袖的引述支持了这一观点：“系统研究需要学术界和工业界更多有潜力的未来领导者”(EPSRC关于系统科学走向工程的研讨会，2011年2月)；安德鲁·霍尔丹(Andrew Haldane)(英格兰银行，2012年)说：“金融危机告诉我们，作为一个复杂的、适应性的系统，对金融进行建模和监管的重要性。这将需要监管界目前很少或缺少的技能--包括重要的复杂性科学领域的技能“；葛兰素史克(GlaxoSmithKline)的Paul Matthews表示，”受过统计和计算方法培训、对生物相关模型有复杂理解的科学家供不应求。他们将是将对人类生物学和疾病的见解转化为治疗和治愈的任务的主要贡献者。“我们的CDT将通过在真实世界系统的背景下培训博士生数学发展和创新来满足这一需求，并将与来自学术界以外的利益相关者密切合作，他们将提供激励性问题和现实世界经验。共同的数学主题将包括复杂系统的统计行为、临界点、控制和弹性方面的新方法、分层汇总方法、模型选择和充分性、网络结构的影响、对非周期性强迫和冲击的反应，以及处理复杂数据的方法。应用程序将由当地和外部合作伙伴在流行病学、系统生物学、作物科学、医疗保健、运筹学、系统工程、网络科学、金融监管、数据分析和社会行为方面的专业知识推动。我们相信，将现实世界的应用与新数学的发展相结合将产生巨大的协同效应；应用将激励和推动数学进步，而新数学将允许学生解决具有挑战性的现实世界问题。博士培养计划将遵循在复杂性科学DTC中被证明成功的1+3年硕士+博士模式。第一年将包括六个月的授课培训，然后是为期三个月的关于外部合作伙伴提出的问题的小组研究项目，以及一个为期三个月的个人研究项目，以获得理学硕士资格。这项准备将使学生能够在一名数学导师和一名应用型导师的指导下，在一般技能培训和小组研究项目的指导下，快速完成他们的三年博士研究项目。我们有50多名具有相关数学专业知识的合适导师，他们都热衷于做出贡献；他们将得到来自整个校园和外部合作伙伴的类似数量的以应用为导向的导师的支持。CDT从EPSRC寻求相当于每年7个全额学生名额，并从非RCUK来源获得相当于每年3个全额学生名额的承诺。

MathSys addresses two of EPSRC's CDT priority areas in Mathematical Sciences: "Mathematics of Highly Connected Real-World Systems" and "New Mathematics in Biology and Medicine". We will train the next generation of skilled applied mathematical researchers to use and develop cutting-edge techniques enabling them to address a range of challenges faced by science, industry and modern society. Our Centre for Doctoral Training will build on the experience and successes of the Complexity Science DTC at Warwick, while refining the scope of problems addressed. It will provide a supportive and stimulating environment for the students in which the common mathematical challenges underpinning problems from a variety of disciplines can be tackled. The need for mathematically skilled researchers, trained in an interdisciplinary environment, has never been greater and is viewed as a major barrier in both industry and government. This is supported by quotes from reports and business leaders: "Systems research needs more potential future leaders, both in academia and industry" (EPSRC workshop on Systems science towards Engineering, Feb 2011); Andrew Haldane (Bank of England, 2012) said "The financial crisis has taught us the importance of modelling and regulating finance as a complex, adaptive system. That will require skills currently rare or missing in the regulatory community - including, importantly, in the area of complexity science"; Paul Matthews (GlaxoSmithKline) stated "Scientists trained in statistical and computational approaches who have a sophisticated understanding of biologically relevant models are in short supply. They will be major contributors in the task of translating insights on human biology and disease into treatments and cures." Our CDT will address this need by training PhD students in the development and innovation of mathematics in the context of real-world systems and will operate in close collaboration with stakeholders from outside academia who will provide motivating problems and real-world experience. Common mathematical themes will include statistical behaviour of complex systems, tipping points, novel methods in control and resilience, hierarchical aggregation methods, model selection and sufficiency, implications of network structure, response to aperiodic forcing and shocks, and methods for handling complex data. Applications will be driven by local and external partner expertise in Epidemiology, Systems Biology, Crop Science, Healthcare, Operational Research, Systems Engineering, Network Science, Financial Regulation, Data Analysis and Social Behaviour. We believe that the merging of real-world applications with development of novel mathematics will have great synergy; applications will motivate and drive mathematical advances while novel mathematics will allow students to solve challenging real-world problems.The doctoral training programme will follow a 1+3 year MSc+PhD model that has proved successful in the Complexity Science DTC. The first year will consist of six months of taught training, followed by 3-month group research projects on problems set by external partners and a 3-month individual research project, leading to an MSc qualification. This preparation will enable the students to make rapid progress tackling their 3-year PhD research project, under the guidance of one mathematical and one application-oriented supervisor, alongside general skills training and group research projects. We have over 50 suitable supervisors with relevant mathematical expertise, all enthusiastic to contribute; they will be supported by a similar number of application-oriented supervisors from across campus and from external partners.The CDT seeks the equivalent of 7 full studentships per year from EPSRC and has commitment from non-RCUK sources for the equivalent of 3 full studentships per year.