TRAINING CROSS DISCIPLINARY LEADERS
Our vision is to equip the leaders of tomorrow with cross-disciplinary quantitative skills to the benefit of industry and society. We train the next generation of quantitative scientists to enable them to develop and calibrate digital twins for real-world real-time decision support in topical physical, physiological, ecological and engineering applications. This will provide the necessary foundations to transform the use of data in industry, academia and the wider society in elucidating complex systems.
Our CDT provides a cross-disciplinary environment where each cohort of students brings together different skills related to physical domain knowledge, mathematical forward modelling and statistical inference, linking closer to experimental and observational data (e.g. from medical imaging, laboratory assays, sensor networks or surveys) and developing novel tools for inference. Uniquely, we will expose our students to all aspects of this process, starting from data generation both in our own labs and those of our external partners.