Mathematical Modelling MSc
This MSc provides an ideal foundation for students wishing to advance their mathematical modelling skills. The programme teaches students the basic concepts which arise in a broad range of technical and scientific problems and illustrates how these may be applied in a research context to provide powerful solutions.
Mode of study
- Full-time 1 year
- Part-time 2 years
- UK/EU Full-time: £8,500
- UK/EU Part-time: £4,250
- Overseas Full-time: £16,750
- Overseas Part-time: £8,500
- All applicants: 1 August 2014
More details in Application section.
What will I learn?
Students develop an understanding of the processes undertaken to arrive at a suitable mathematical model and are taught the fundamental analytical techniques and computational methods used to develop insight into system behaviour. The programme introduces a range (e.g. industrial, biological and environmental) of problems, associated conceptual models and their solutions.
Why should I study this degree at UCL?
UCL Mathematics is internationally renowned for its excellent individual and group research that involves applying modelling techniques to problems in industrial, biological and environmental areas.
The department hosts a stream of distinguished international visitors. In recent years four staff members have been elected fellows of the Royal Society, and the department publishes the highly regarded research journal Mathematika.
This MSc enables students to consolidate their mathematical knowledge and formulate basic concepts of modelling before moving on to case studies in which models have been developed for issues motivated by industrial, biological or environmental considerations.
Students undertake modules to the value of 180 credits. The programme consists of five core modules (75 credits), three optional modules (45 credits), and a research dissertation (60 credits).
The part-time option normally spans two years. The eight taught modules are spread over the two years. The research dissertation is taken in the summer of the second year.
An exit-level Postgraduate Diploma (120 credits, full-time one year) is offered.
All MSc students undertake an independent research project, which culminates in a dissertation of approximately 15,000 words and a project presentation.
Teaching and Learning
The programme is delivered through seminar-style lectures and problem and computer-based classes. Student performance is assessed through a combination of unseen examination and coursework. For the majority of courses, the examination makes up between 90–100% of the assessment. The project is assessed through the dissertation and an oral presentation.
Further details available on subject website:
A minimum of an upper second-class Bachelor's degree in a relevant discipline from a UK university or an overseas qualification of an equivalent standard.
Select your country for equivalent alternative requirements
English language proficiency level: Standard
How to apply
Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.
The deadline for applications is 1 August 2014.
Who can apply?
The programme is aimed at students with a background in a highly numerate disciplinethat wish to advance their mathematical modelling skills. Successful students will be well placed to satisfy the growing demand for mathematical modelling in commerce and industry, and will learn and practice the skills necessary to pursue further research.
What are we looking for?
When we assess your application we would like to learn:
- why you want to study Mathematical Modelling at graduate level
- why you want to study Mathematical Modelling at UCL
- what particularly attracts you to this programme
- how your academic background meets the demands of a challenging programme
- where you would like to go professionally with your degree
Our graduates have found employment in a wide variety of organisations such as Hillier-Parker, IBM, Swissbank, Commerzbank Global Equities, British Gas, Harrow Public School, Building Research Establishment and the European Centre for Medium-Range Weather-Forecasting. First destinations of recent graduates include:
- R.T.E: Engineer
- Tower Perrins: Actuarist
- Deloitte: Quantitative Analyst
- UCL: Research Associate
- C-View: Quantitative Trader
- One-to-One: Maths Tutor
- UCL Research Degree - Mathematics
- Duff & Phelps Ltd: Financial Engineer
- Bank of Tokyo Mitsubishi: Assistant Compliance Officer
Top career destinations for this programme
- Hed Capital, Financial Modelling Analyst, 2011
- UCL, PhD in Biology and Mathematics, 2010
- RTE, Engineer, 2009
- Tower Perrins, Actuarist, 2009
- Deloitte, Quantitative Analyst, 2009
The finance, actuarial and accountancy professionals are constantly in demand for high-level mathematical skills and recent graduates have taken positions in leading finance-related companies such as UBS, Royal Bank of Scotland, Societe Generale, PricewaterhouseCoopers, Deloitte, and KPMG.
In the engineering sector, recent graduates from the MSc include a mathematical modeller at Steet Davies Gleave, a leading Transportation Planning Consultancy, and a graduate trainee at WesternGreco, a business segment of Schlumberger that provide recervoir imaging, monitoring, and development services.
In addition, a number of graduates have remained in education either progressing to a PhD or entering the teaching profession.
Professor Frank Smith
T: +44 (0)20 7679 4102
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"Many of the world's top researchers visit London because of its strength in geometry and mathematics in general, so I have been able to network with top names in the field, leading to long-lasting connections and collaborations."
Dr Jason Lotay
Lecturer in Pure Mathematics
"Science and Technology Studies (STS) is a meeting point of different disciplines influencing our daily life and UCL’s multi-disciplinary approach to the STS allowed me to have a greater perspective."
Degree: Science, Technology, Medicine and Society MSc
Subject: Science and Technology Studies, Faculty: Mathematical and Physical Sciences