PROGRAMME / 02
Master · Artificial Intelligence and Numerical Modelling
Use applied mathematics, scientific computing and AI to build, solve and optimise models for complex scientific and engineering problems.
For applicants with relevant prior study. Develop advanced technical and research skills. Planned workload: 120 credits.
YEAR 01Advanced Scientific Computing
- Computational Partial Differential Equations
- Physics-Informed Neural Networks
- Inverse Problems and Regularisation
- High-Performance Computing
- Advanced Optimisation
- Research Methods
YEAR 02Model Integration and Research
- Neural Operators
- Model Order Reduction
- Multiscale Modelling
- Data Assimilation
- Uncertainty Quantification
- Master’s Dissertation and Defence
SHARED LEARNING
Shared foundations. Specialist depth.
Share AI, optimisation and parallel computing modules, with dynamical systems and model validation shared with the digital twins pathway.
Specialist focus: Mathematical formulation, numerical solutions, error analysis and scientific machine learning.
Assessment and outcomes
Evaluate assumptions, accuracy, stability and efficiency. Validate against analytical solutions, benchmarks, experimental data or independent methods, and explain the limits of the model.
Develop a scientific or engineering model, solve and calibrate it, analyse errors, and deliver executable code with a validation report.