Course summary
Our MSc Advanced Mathematical Modelling is an advanced course that offers the opportunity to develop skills in understanding, predicting, and solving complex real-world problems. From climate modelling and fluid dynamics to medical applications and engineering design, the ability to develop and analyse mathematical models is in high demand across industries and research sectors. This MSc is designed for students who want to apply advanced mathematical techniques to practical challenges. The programme offers:
- a strong foundation in applied mathematics, including mathematical biology, fluid dynamics, numerical analysis, and machine learning
- hands-on experience in developing and analysing models that describe real-world systems
- training in both analytical and computational techniques, ensuring graduates have a versatile skill set
- the opportunity to undertake an individual research project, working on cutting-edge problems in collaboration with academic staff and potentially industry partners
Modules
Modelling & Simulation with Applications to Financial Derivatives Applicable Analysis 3 Fluids & Waves Finite Element Methods for Boundary Value Problems & Approximation Optimisation: Theory Applied Mathematical Methods 1 Foundations of Statistics Mathematics of Machine Learning Mathematical Biology & Marine Population Modelling Mathematical Introduction to Networks Optimisation for Analytics Numerical Methods & Deep Learning Algorithms for Partial Differential Equation Medical Statistics Effective Statistical Consultancy Survey Design & Analysis Quantitative Risk Analysis Bayesian Spatial Statistics Statistical Machine Learning Data Dashboards with RShiny Deep Learning Research Project
Assessment method
The form of assessment varies across modules. For most modules, the assessment involves both coursework and practical computer-based or written examinations. The assessment will require you to demonstrate your computational and mathematical knowledge to model and analyse a suitable situation, and to interpret the results in the context of the research question. Projects will involve writing code, interpreting outputs, and producing a report, interactive visualisation or presentation outlining the findings from your analysis. Group work may be undertaken in some modules. There is also a graded research dissertation.
Entry requirements
Minimum second-class (2:2) honours degree or overseas equivalent* in Mathematics, Computer Science or a closely related discipline containing a strong Mathematical component. Prospective students with relevant experience or appropriate professional qualifications are also welcome to apply. *For Australia and Canada, normal degrees are accepted.
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Sponsorship information
https://www.strath.ac.uk/studywithus/scholarships/
Provider information
University of Strathclyde
McCance Building
16 Richmond Street
Glasgow
G1 1XQ