Program Overview

MSc Advanced Computational Mathematics

The MSc Advanced Computational Mathematics is an advanced course that offers the opportunity to develop understanding of computational mathematics and numerical analysis, enabling students to model complex real-world problems. The course combines theoretical foundations with practical computing skills, making students highly employable in finance, technology, and scientific computing.

Key Facts

• Start date: September
• Application deadline: September
• Study mode and duration: on campus, 12 months full-time

Why this Course?

Our MSc Advanced Computational Mathematics is designed for students with a strong background in mathematics, computational science, or numerical methods. The course develops expertise in computational methods, algorithm development, machine learning theory, and numerical methods, providing students with computational skills highly sought after in finance, engineering, and data-driven industries.

What you’ll Study

In addition to compulsory modules, there are a range of elective modules, allowing students to tailor the course in line with their career interests.

Semester 1

Modules focus on a strong foundation in computational techniques, including finite element methods for boundary value problems and machine learning mathematics. These modules equip students with the theoretical and practical skills needed for advanced numerical computing.

Semester 2

The focus shifts to numerical methods and deep learning for partial differential equations, expanding students' understanding of algorithmic approaches to complex mathematical problems.

Semester 3

Dedicated to a research project, where students apply their computational mathematics skills to tackle a real-world problem. This project is an excellent opportunity to develop independent research abilities and engage with industrial or academic applications.

Learning & Teaching

Classes are delivered by a variety of teaching methods, including:

• Lectures
• Tutorials
• Computer laboratories
• Coursework
• Projects

Teaching is student-focused, with students encouraged to take responsibility for their own learning and development. Classes are supported by web-based materials.

Assessment

The form of assessment varies from class to class, involving both coursework and practical computer-based or written examinations.

Facilities

The Department of Mathematics & Statistics has teaching rooms with modern teaching equipment and University computing laboratories, with all necessary software available. Students also have access to a common room facility for individual and group study work and socializing.

The Department of Mathematics & Statistics

At the heart of the Department of Mathematics & Statistics is the University’s aim of developing useful learning. The department is applied, with many links to industry and government, and most academic staff teaching on this course hold joint-appointments with, or are funded by, other organizations.

Course Content

Throughout their studies, students take 60 credits of compulsory taught modules, 60 credits of elective taught modules, and in the third term, undertake an MSc Project (60 credits).

Compulsory Modules

• Finite Element Methods for Boundary Value Problems & Approximation
• Numerical Methods & Deep Learning Algorithms for Partial Differential Equation
• Mathematics of Machine Learning

Elective Modules

A range of modules are available, including but not limited to:

• Modelling & Simulation with Applications to Financial Derivatives
• Applicable Analysis 3
• Optimisation: Theory
• Big Data Fundamentals
• Big Data Tools & Techniques
• Legal, Ethical and Professional Issues for the Information Society
• Data Analytics in R
• Foundations of Statistics
• Mathematical Introduction to Networks
• Optimisation for Analytics
• Medical Statistics
• Quantitative Risk Analysis
• Bayesian Spatial Statistics
• Statistical Machine Learning
• Data dashboards with RShiny
• Deep Learning

Entry Requirements

• Academic requirements/experience: Minimum second-class (2:2) Honours degree or overseas equivalent in mathematics, computer science, or a closely related discipline.
• English language requirements: IELTS 6.0 (with no component below 5.5).

Fees & Funding

• Scotland: £11,900
• England, Wales & Northern Ireland: £11,900
• Republic of Ireland: Same as England, Wales & Northern Ireland
• International: £25,500
• Additional costs: Visa and immigration costs for international students.

Careers

Studying a postgraduate programme in maths and computing helps students further develop skills in logical thinking and statistical or strategic knowledge, which are valued by employers across many job sectors. Graduates enter industries such as aerospace and software engineering, manufacturing, the actuarial, accountancy, and banking professions, commerce and government, consultancy, and education. Many go on to work as financial analysts, software developers, accountants, operations analysts, treasury analysts, auditors, and management trainees. A master's degree in mathematics and computing is desirable to a wide range of employers who recruit from any degree subject. It is also useful for those considering a more general business career.