A new doctoral training centre at the University of Southampton will teach the next generation of researchers how to build and use computer simulations to tackle complex real-world problems—from climate change to drug design. The problem is that while cheap computing power now makes simulation accessible to almost any scientist, training in how to use it rigorously is patchy and fragmented across isolated research fields. Researchers often build models without understanding the strengths and weaknesses of different simulation approaches, or how simulation relates to mathematical modelling and physical experiments. This gap threatens to produce a generation of researchers who can run simulations but cannot do so effectively or reliably. If the centre succeeds, it will create a community of doctoral graduates who act as research leaders across climate science, pharmaceuticals, biosciences, nanoscience, transport, engineering, and medical systems. These are domains where simulation already underpins decisions about infrastructure, energy grids, supply chains, and medical diagnostics. Better-trained researchers mean more reliable models, fewer costly design failures, and faster progress on systemic challenges—such as making a city’s transport network resilient to disruption or predicting how a new drug will behave in the body.
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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.
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