Course summary

Our Predictive Modelling and Scientific Computing MSc trains students in the theory and practical implementation of cutting-edge predictive modelling techniques, exposing them to established, as well as emerging, applications in science and engineering. Predictive Modelling is a fusion of mathematical modelling, machine learning and scientific computing, providing a powerful new way of thinking about how to model complex systems and improve technology and design. Enhancements in computer processing power and access to ‘Big Data’ have led to a growth in the number of applications of predictive modelling into areas as diverse as environmental science, energy, healthcare, materials engineering, food science and geology. Our MSc in Predictive Modelling and Scientific Computing educates future specialists in computational science and engineering, equipping them to apply appropriate computational techniques to understand, define and develop solutions to a range of science and engineering problems, including those of national and global importance. Core modules cover uncertainty quantification, predictive modelling and scientific computing, whilst the choice of three optional modules gives students the opportunity to specialise the application focus of the course to align with their interests. Students will participate in individual and group research projects, as well as writing reports and presenting technical work, thus developing the project management and numerical skills sought by employers. The MSc can be studied part-time over two years to suit those in employment. PG Diploma, Certificate and Award options are also available for those who would like to take a subset of modules. This course is new for entry in 2023 and will equip graduates for further study in areas of critical science and technological importance, or for employment in a broad range of data-intensive industries where modelling, design and decision making under uncertainties is important. We have strong links with a range of potential employers.