EPSRC Centre for Doctoral Training in Mathematics of Random Systems: Analysis, Modelling and Simulation

EPSRC 随机系统数学博士培训中心：分析、建模和仿真

• 批准号: EP/S023925/1
• 金额: $ 879.31万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Training Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FS023925%2F1
• 关键词: EPSRC; Centre; Doctoral; Training; Mathematics

Probabilistic modelling permeates all branches of engineering and science, either in a fundamental way, addressing randomness and uncertainty in physical and economic phenomena, or as a device for the design of stochastic algorithms for data analysis, systems design and optimisation. Probability also provides the theoretical framework which underpins the analysis and design of algorithms in Data Science and Artificial Intelligence. The "CDT in Mathematics of Random Systems" is a new partnership in excellence between the Oxford Mathematical Institute, the Oxford Dept of Statistics, the Dept of Mathematics at Imperial College and multiple industry partners from the healthcare, technology and financial services sectors, whose goal is to establish an internationally leading PhD training centre for probability and its applications in physics, finance, biology and Data Science, providing a national beacon for research and training in stochastic modelling and its applications, reinforcing the UK's position as an international leader in this area and meeting the needs of industry for experts with strong analytical, computing and modelling skills.We bring together two of the worlds' best and foremost research groups in the area of probabilistic modelling, stochastic analysis and their applications -Imperial College and Oxford- to deliver a consolidated training programme in probability, stochastic analysis, stochastic simulation and computational methods and their applications in physics, biology, finance, healthcare and Data Science. Doctoral research of students will focus on the mathematical modelling of complex physical, economic and biological systems where randomness plays a key role, covering mathematical foundations as well as specific applications in collaboration with industry partners. Joint projects with industrial partners across several sectors -technology, finance, healthcare- will be used to sharpen research questions, leverage EPSRC funding and transfer research results to industry.Our vision is to educate the next generation of PhDs with unparalleled, cross-disciplinary expertise, strong analytical and computing skills as well as in-depth understanding of applications, to meet the increasing demand for such experts within the Technology sector, the Financial Service sector, the Healthcare sector, Government and other Service sectors, in partnership with industry partners from these sectors who have committed to co-funding this initiative. ALIGNMENT with EPSRC PRIORITIES This proposal reaches across various areas of pure and applied mathematics and Data Science and addresses the EPSRC Priority areas of (15. Mathematical and Computational Modelling), (22. Pure Mathematics and its Interfaces) ; however, the domain it covers is cross-disciplinary and broader than any of these priority areas taken in isolation. Probabilistic methods and algorithms form the theoretical foundation for the burgeoning area of Data Science and AI, another EPSRC Priority area which we plan to address, in particular through industry partnerships with AI/technology/data science firms.IMPACTBy training highly skilled experts equipped to build, analyse and deploy probabilistic models, the CDT in Mathematics of Random Systems will contribute to- sharpening the UK's research lead in this area and training a new generation of mathematical scientists who can tackle scientific challenges in the modelling of complex, simulation and control of complex random systems in science and industry, and explore the exciting new avenues in mathematical research many of which have been pioneered by researchers in our two partner institutions;- train the next generation of experts able to deploy sophisticated data driven models and algorithms in the technology, finance and healthcare sectors

概率建模渗透到工程和科学的所有分支，无论是以基本的方式，解决物理和经济现象中的随机性和不确定性，还是作为数据分析，系统设计和优化的随机算法设计的设备。概率还提供了支撑数据科学和人工智能算法分析和设计的理论框架。“随机系统数学中的CDT”是牛津数学研究所，牛津统计学系，帝国理工学院数学系与来自医疗保健，技术和金融服务部门的多个行业合作伙伴之间的新合作伙伴关系，其目标是建立一个国际领先的概率及其在物理，金融，生物学和数据科学中的应用的博士培训中心，为随机建模及其应用的研究和培训提供国家灯塔，加强英国在这一领域的国际领导地位，并满足行业对具有强大分析，计算和建模技能的专家的需求。我们汇集了世界上最好和最重要的两个研究小组在概率建模领域，随机分析及其应用-帝国理工学院和牛津大学-提供概率，随机分析，随机模拟和计算方法及其在物理，生物学，金融，医疗保健和数据科学中的应用的综合培训计划。学生的博士研究将侧重于随机性发挥关键作用的复杂物理，经济和生物系统的数学建模，涵盖数学基础以及与行业合作伙伴合作的具体应用。与多个行业的工业合作伙伴的联合项目-技术，金融，医疗保健-将用于尖锐的研究问题，利用EPSRC的资金和研究成果转移到行业。我们的愿景是教育下一代博士具有无与伦比的，跨学科的专业知识，强大的分析和计算技能，以及对应用的深入理解，满足技术部门、金融服务部门、医疗保健部门、政府和其他服务部门对此类专家日益增长的需求，与这些部门的行业合作伙伴合作，共同资助这一倡议。与EPSRC优先事项的一致性本提案涉及纯数学和应用数学以及数据科学的各个领域，并解决了EPSRC的优先领域（15.数学和计算模型（22）。纯数学及其接口）;然而，它所涵盖的领域是跨学科的，比孤立地考虑的任何这些优先领域都要广泛。概率方法和算法构成了新兴的数据科学和人工智能领域的理论基础，这是我们计划解决的另一个EPSRC优先领域，特别是通过与人工智能/技术/数据科学公司的行业合作伙伴关系。影响通过培训具备构建，分析和部署概率模型的高技能专家，CDT在随机系统数学将有助于-锐化英国在这一领域的研究领先地位，并培养新一代的数学科学家谁可以解决复杂的建模科学挑战，模拟和控制科学和工业中的复杂随机系统，并探索数学研究中令人兴奋的新途径，其中许多是由我们两个合作机构的研究人员开创的;-培养下一代专家，能够在技术，金融和医疗保健领域部署复杂的数据驱动模型和算法