Predictive Modelling and Scientific Computing (Taught)

Train in the theory and practical implementation of cutting-edge predictive modelling techniques.

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, building on students’ existing programming skills and 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.

This course will equip graduates for further study in areas of critical science and technological significance, 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.

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 information is applicable for 2026 entry. Given the interval between the publication of courses and enrolment, some of the information may change. It is important to check our website before you apply.

Core modules

• Fundamentals of Predictive Modelling (ES98A) (15 credit)
• Numerical Algorithms and Optimisation (MA934) (15 credit)
• Scientific Machine Learning (ES98E) (15 credit)
• Predictive Modelling Group Project (ES98B) (30 credit)
• Individual Research Project (ES98C) (60 credit)

Optional modules
The selection of optional modules is likely to include:

• Modelling and Computation of Fluid Dynamics Across Phases and Scales (MA9M4)*
• Particle-based Modelling (ES98D)*
• Predictive Modelling of Advanced Engineering Materials*
• High Performance Computing
• Statistical Learning and Big Data
• Advanced Topics in Fluids
• Advanced Computational Chemistry
• Biomolecular Simulation
• Biomedical Systems Modelling

*Please note that students are required to take at least one of these three optional modules.

PG Diploma, Certificate and Award options are also available for those who would like to take a subset of modules. More information can be found on our website.

You will experience a variety of assessment methods, and can expect to mostly sit (online or face-to-face) examinations and complete coursework assignments.