Course summary

To equip you with the key skills towards becoming a world-leading design engineering researcher, the MRes in Design Engineering Research offers an exciting collection of taught modules leading towards the execution of a major research project. The Design Engineering Practice module will equip you with key design engineering tools and practices that allow you to systematically handle and embrace uncertainty. The Modelling and Simulation module will teach you how to describe complex systems mathematically, towards simulating their behaviours and then apply probabilistic principles from Game Theory towards understanding the impact of decisions and how uncertainty propagates through the system. Foundational Transdisciplinary Research Methods and Advanced Transdisciplinary Research Methods then formally introduce you to what transdisciplinary research is, as well as a mixture of qualitative and quantitative research tools that allow you to engage a diverse set of stakeholders towards generating rich insights. Here tools start from qualitative topics such as interviews, narrative studies and ethnographic approaches, as well as quantitative tools such as frequentist descriptive/inferential statistics, experiment design and survey design. This then builds to more advanced tools such as Bayesian inference, statistical modelling and reflexivity, leading to the exploration of emerging machine learning tools such as text mining, sentiment analysis and natural language processing. In doing this, you will gain a critical understanding of the role of the researcher and the various types of tools in research. You will have the option of deepening your subject-specific knowledge with the selection of two elective modules which span a diverse set of topic areas, including Machine Learning for Design Engineers, Design for Additive Manufacturing, Design Psychology, Design Analytics for the Sharing Economy, Designing Interventions for Behaviour Change and others.