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、紧迫的现实挑战以及利用前所未有的计算能力的机会所推动的。在复杂系统仿真（CSS）的南安普顿DTC将是第一个联合收割机明确，互补和综合培训这三个组成部分在跨学科博士研究项目的背景下。这将推动使能模拟技术和复杂性科学方法的进步，以及气候、制药、生物科学、纳米科学、医疗和化学系统、运输、工程和计算等关键应用领域的实时研究问题。与以原子、遗传和分子科学为代表的还原论研究计划在世纪取得的巨大成功相比，在即将到来的世纪，系统科学和工程将越来越受到重视，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、恢复力和可进化性等问题。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。随着廉价的计算能力的可用性，模拟建筑正在成为一个可行的选择，为博士生在广泛的学科。然而，重要的是要认识到，如何最好地部署计算资源来理解复杂的目标系统的培训目前非常零散，反映了复杂性科学研究目前在相对孤立的研究领域中进行的分散性。虽然下一代研究人员肯定会使用强大的模拟，但尚不清楚他们是否会有效和严格地使用它们。这种情况必须立即得到解决，办法是在足够数量的研究人员中巩固最佳做法，必须在适当的复杂系统领域内，针对实际研究挑战提供有效的培训。它必须解决技术实施问题，以及如何利用高性能计算的最新技术，但也要灌输广泛的方法复杂性。特别是，仿真，数学建模和实验之间的相互依存关系的命令是至关重要的，因为是从有限元方法，通过多尺度模型和系统的系统方法，以代理为基础的建模，从用于解决数学模型的有效数值方法，通过抽象的计算思维实验，到现实的预测仿真模型。为了实现这一目标，南安普顿DTC CSS将产生一个博士毕业生社区，他们将成为将复杂系统模拟应用于21世纪最紧迫的科学和工程挑战的研究领导者。

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.