A Doctoral Training Centre in Complex Systems Simulations

当前复杂性科学研究的激增是由新理论、紧迫的现实世界挑战以及利用前所未有的计算能力的机会推动的。南安普敦复杂系统仿真DTC将在跨学科博士研究项目的背景下，第一个将这三个部分的明确、互补和综合培训结合在一起。这将推动使能模拟技术和复杂性科学方法论的进步，以及跨越气候、制药、生物科学、纳米科学、医疗和化学系统、运输、工程和计算的关键应用领域的实时研究问题。与以原子、基因和分子科学为代表的简化论研究计划的巨大成功相比，下个世纪将看到越来越多的人关注系统科学和工程，目标是物理、生物、环境、社会和技术系统及其相互作用，并解决系统功能、组织、管理、稳定性、弹性和进化性等问题。除了跨学科和高通量实验，模拟建模已经成为解决这些问题的关键工具。随着廉价计算能力的现成，模拟构建正在成为各种学科的博士生的可行选择。然而，关键是要认识到，关于如何最好地部署计算资源以了解复杂目标系统的培训目前非常零散，反映了目前跨相对孤立的研究领域开展的复杂性科学研究的碎片化性质。虽然下一代研究人员肯定会使用强大的模拟，但目前还不清楚他们是否会有效和严格地使用它们。这种情况必须立即通过整合大量研究人员的最佳实践来解决。必须在适当的复杂系统领域内的现场研究挑战的背景下提供有效的培训。它必须解决技术实现以及如何在高性能计算中利用最新技术的问题，但也必须灌输广泛的方法复杂性。特别是，掌握仿真、数学建模和实验之间的相互依赖关系是至关重要的，因为掌握仿真建模方法的不同优缺点也是至关重要的，仿真建模方法的范围从有限元方法到多尺度模型和系统系统方法到基于代理的建模，以及从通过抽象计算思维实验求解数学模型的高效数值方法到现实的预测模拟模型。为了实现这一目标，南安普敦DTC CS将培养一批博士毕业生，他们将作为研究领导者，将复杂的系统模拟应用于21世纪最紧迫的科学和工程挑战。

The current surge in complexity science research is being driven by new theory, pressing real-world challenges and the opportunity to exploit an unprecedented availability of computational power. The Southampton DTC in Complex Systems Simulation (CSS) will be the first to combine explicit, complementary and integrated training in these three components in the context of interdisciplinary doctoral research projects. This will drive progress in both the enabling simulation technologies and complexity science methodology, as well as live research questions in key application domains spanning climate, pharma, biosciences, nanoscience, medical and chemical systems, transport, engineering & computing.In contrast to the twentieth century's huge success in reductionist research programmes epitomised by atomic, genetic and molecular science, the coming century will see an increasing focus on systemic science and engineering, targeting physical, biological, environmental, social, and technological systems and their interactions, and addressing questions of system function, organisation, management, stability, resilience, and evolvability. Alongside interdisciplinarity and high-throughput experimentation, simulation modelling is already emerging as the key tool for addressing such questions. With the ready availability of cheap computational power, simulation building is becoming a viable option for doctoral students across a wide range of disciplines. However, it is critical to recognise that training in how best to deploy computational resources to understand complex target systems is currently extremely patchy, reflecting the currently fragmented nature of complexity science research being carried out across relatively isolated research domains. While the next generation of researchers will certainly be using powerful simulations it is not yet clear that they will be using them effectively and rigorously. This situation must be addressed immediately by consolidating best practice in a critical mass of researchers.Effective training must be delivered in the context of live research challenges within appropriate complex systems domains. It must address issues of technical implementation and how to exploit the state of the art in high-performance computing, but also inculcate broad methodological sophistication. In particular, command of the interdependent relationship between simulation, math modelling, and experimentation is crucial, as is a grasp of the different strengths and weaknesses of simulation modelling approaches ranging from finite element methods through multi-scale models and systems-of-systems approaches to agent-based modelling, and from efficient numerical methods for solving math models through abstract computational thought experiments to realistic predictive simulation models. In achieving this, the Southampton DTC CSS will generate a community of doctoral graduates equipped to act as research leaders in applying complex systems simulation to the most pressing scientific and engineering challenges of the 21st century.