MSc Applied Mathematics

1 Year On Campus Masters Program

Imperial College London

Program Overview

Program Overview:
The MSc in Applied Mathematics at Imperial offers you rigorous training in mathematical modelling, analysis, and computation ideal if you enjoy solving real-world problems across physics, biology, engineering, or data science. The programme is highly flexible, letting you tailor your studies to your background and interests while developing strong problem-solving and research skills.

Curriculum structure:
Over the course of the degree, you follow a mix of taught modules and a research project, giving both breadth and depth in applied mathematics.

Year-by-year (or phase) breakdown:

In the taught-courses phase (autumn and spring), you pick 8 modules (or 4 per year if part-time) from a large selection ranging from numerical analysis, differential equations, stochastic processes, mathematical biology, to optimisation and machine learning letting you focus on what matters to you most.
Modules such as Computational Partial Differential Equations, Computational Linear Algebra, Methods for Data Science (and many others) give you hands-on and theoretical tools to tackle PDEs, numerical methods, data-driven modelling, and computational problems.
In the summer (or final phase), you undertake an independent research project aligned with your chosen modules (or, if on the SCML stream, aligned with computational/data-driven mathematics) this lets you apply what you learned to a significant piece of original work.

Focus areas:
Applied & stochastic analysis; numerical analysis; scientific computation; partial differential equations; mathematical biology; data science & machine learning; optimisation; fluid dynamics; mathematical physics (depending on your module choices).

Learning outcomes:
Students graduate with strong skills in mathematical modelling, computational and analytical methods, numerical solution of differential equations, data-driven and machine-learning approaches (if chosen), and the ability to carry out independent research and present advanced mathematical arguments.

Professional alignment (accreditation):
The programme is delivered by the Department of Mathematics at Imperial, a globally recognised institution; the skills gained align with careers in research, academia, engineering, data science, quantitative finance, computational science and more.

Reputation (employability / rankings):
Imperial College London consistently ranks among the top universities worldwide for science and engineering. As part of its mathematics department, this MSc benefits from Imperial’s strong reputation and high employability outcomes for graduates a degree from Imperial is widely respected in academia and industry alike.

Experiential Learning (Research, Projects, Internships etc.)

As a student on the Applied Mathematics MSc at Imperial, you don’t just study theory — you get hands-on experience using professional computational tools and tackle real research problems, all supported by excellent facilities and faculty supervision. The programme is designed to build the kinds of analytical, modelling and computational skills that employers — and cutting-edge research groups — actually value.

Here’s what that looks like in practice:

Access to dedicated computing labs and study spaces: As part of the course you’ll have access to an MSc-student computer room / common room, as well as a dedicated Mathematics Learning Centre with ~64 computers, study desks fitted with audio-visual facilities for presentations, printers, and quiet/study rooms.
Strong library and online resource support: Students benefit from the Abdus Salam Library (open 24 hours) and other campus libraries, with access to hundreds of thousands of books, e-books, e-journals and databases — essential for research projects, reading, and independent study.
Wide choice of modules — including computational and data-driven streams: Beyond classical applied mathematics, you can choose from a broad set of modules (e.g. computational partial differential equations, numerical analysis, finite elements, mathematical foundations of machine learning, methods for data science, optimisation, stochastic processes, etc.). This lets you tailor your learning to interest areas — whether that’s fluid dynamics, mathematical biology, machine learning, finance, or physics.
Option to specialise in computational mathematics + machine learning (SCML stream): If you’re interested in the interface between computational mathematics and data-driven modelling, the programme offers a specialised stream (SCML). Through this you can gain core expertise in modern computational techniques and machine learning applied to real mathematical problems.
Substantial independent research project under academic supervision: A major component of the MSc is an independent research project. You pick a topic — with a supervisor — after the first term, then work on it over second term and summer. The project ends with a written dissertation plus a presentation (and often a viva-like oral component). Some past projects have even led to publications.
Teaching and assessment methods that foster active learning: The programme uses a mix of lectures, problem classes / problem sheets, group tutorials, self-study, seminars, and individual consultations. That means you aren’t just passively absorbing knowledge — you actively work through problems, discuss with peers, and apply what you learn.

Progression & Future Opportunities

Graduate outcomes (summary)
Graduates from Imperial’s MSc in Applied Mathematics routinely secure skilled roles many enter fields like finance, data science, quantitative analysis, or engineering and a significant proportion go on to further research or PhD studies. With a robust foundation in advanced applied mathematics, modelling and computation, they’re well positioned for both industry and academia.

Career paths you could take after graduation include:

Quantitative Analyst / Quantitative Researcher (finance, risk analysis, financial modelling)
Data Scientist / Machine-Learning Engineer (especially through the SCML stream)
Mathematical / Computational Modeler in industries such as aerospace, energy, or engineering
Research Scientist (academic or industrial R&D), or postgraduate researcher (PhD route)

Because:

University support and employability services: The Department of Mathematics and Imperial’s Careers service guide students in gaining relevant work experience, internships, and employability skills (e.g. communication, coding, teamwork). Employment statistics & outcomes: According to the most recent data for taught postgraduates in Mathematics at Imperial, in 2023 about 82% entered employment within a year of graduation.
Industry & sector reach: Graduates have entered sectors including finance/insurance, IT & communications, professional/scientific technology, and technical consultancy reflecting broad demand for their skills.
Long-term accreditation and academic / professional value: The MSc gives you a strong, widely respected mathematical foundation, combining core theory with modern computational and data-driven approaches (through the optional Scientific Computing & Machine Learning stream) a skill set highly valued by both employers and academic institutions.
Versatile graduate outcomes: The training is not narrowly specialised you could apply your mathematical, modelling and programming skills to finance, tech, engineering, data science, research or further studies. The broad module choices allow tailoring to your interests.

Further Academic Progression:
You could build on this MSc by pursuing a PhD in applied mathematics, mathematical physics, computational science, or related fields (engineering, data science, mathematical modelling). Alternatively, you might pivot into interdisciplinary postgraduate degrees for example in computational finance, data science, machine learning, or engineering — using your strong mathematical and modelling background as a solid springboard.