The Master of Science in Mathematics (120 ECTS) is a research-based master’s programme in which you can specialize in the following fields of mathematics: Pure Mathematics: Algebra, Analysis and Geometry; and Applied Mathematics: Statistics, Financial Mathematics, Computational Mathematics, Plasma-Astrophysics.
Besides a solid, all-round education in mathematics, the programme offers you the possibility to focus on either pure or applied mathematics. This allows you to acquire both breadth of knowledge and depth in your own areas of interest. Pure and applied mathematics courses are firmly grounded in the core research activities of the Department of Mathematics. Gradually, you will gain experience and autonomy in learning how to cope with new concepts, higher levels of abstraction, new techniques, new applications, and new results. This culminates in the Master’s thesis, where you become actively involved in the research performed in the various mathematical research groups of the Departments of Mathematics, Physics, Astronomy and Computer Sciences.
This is an initial Master's programme and can be followed on a full-time or part-time basis.
The programme of the Master of Science in Mathematics consists of 120 ECTS. You choose one of the two profiles – Pure Mathematics or Applied Mathematics (54 ECTS) – and one of the two options – Research Option or Professional Option (30 ECTS). The profile allows you to specialize either in pure mathematics (algebra, geometry, analysis), or in applied mathematics (statistics, computational mathematics, fluid dynamics).
There is one common course: ‘Mathematics of the 21st Century’ (6 ECTS). To complete the programme, you carry out a research project that results in a master’s thesis (30 ECTS).
All staff members of the Department of Mathematics are actively involved in the two-year Master of Science in Mathematics programme. The academic staff at the Department of Mathematics consists of leading experts in their fields. Researchers in pure mathematics focus on algebraic geometry, group theory, differential geometry, functional analysis, and complex analysis. Researchers in mathematical statistics deal with extreme values, robust statistics, non-parametric statistics, and financial mathematics. Research in the applied mathematics group is in computational fluid dynamics and plasma-astrophysics.
Mathematicians find employment in industry and in the banking, insurance, and IT sectors. Many graduates from the research option pursue a career in research and start a PhD in mathematics, mathematical physics, astrophysics, engineering, or related fields.
The master’s programme Mathematics focuses on analysis and number theory. From applied to fundamental research, and from algebra to data science, our master’s programme spans these fields entirely.
The two-year master's programme Mathematics has two components: an analysis-oriented component with topics such as dynamical systems, differential equations, probability theory and stochastics, percolation and mathematics in the life sciences, and an algebra/geometry-oriented component with topics such as algebraic number theory, algebraic geometry, algebraic topology and cryptology. The goal of each programme is to train the student as an independent researcher, and to develop the necessary skills and proficiency to advance your career.
Read more about our Mathematics programme.
Find more reasons to choose Mathematics at Leiden University.
The master’s programme in Mathematics in Leiden focuses on analysis, probability and statistics, number theory and (arithmetic) geometry. If you are looking for an opportunity to specialize in one of these areas, Leiden is an excellent possibility. Students who have obtained a Master of Science degree in Mathematics possess a thorough theoretical basis, know how to work in a multinational environment, and are able to operate well on the international market.
Read more about the entry requirements for Mathematics.
The MSc in Medical Statistics combines in-depth training in mainstream advanced statistical modelling with a specialisation in medical applications.
This flexible degree programme allows you to blend theoretical and applied statistical disciplines, ideal for training in medical statistics. It combines compulsory and optional modules allowing you to train in a range of statistical techniques (and transferable skills) suitable for either careers in medical statistics and research-related professions, or for further academic research.
Options within the course vary from mainstream topics in statistical methodology to more specialised areas such as epidemiology and biostatistics.
You can also study this programme part time over 24 months.
If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.
Accreditation from the Royal Statistical Society is pending.
The first two semesters of your course will consist of taught modules, and in the third semester you’ll devote your time to a major dissertation in statistics or a research project in applied epidemiology and biostatistics. Within each semester you have the opportunity to choose from a range of optional modules, allowing you to specialise in the area of study of most interest to you.
You’ll be taught by experts from the School of Mathematics, The Centre for Epidemiology and Biostatistics, and The Clinical Trials Research Unit at Leeds, each bringing a different perspective to the subject of medical statistics.
You’ll be supervised for both your taught modules and your research project by professionals across the teaching units and you will be given the opportunity to utilise existing links with individual clinicians and medical research groups in the University of Leeds, Leeds NHS trust, and the Department of Health’s Information Centre in Leeds.
Throughout the course you’ll learn about new developments in statistics and be provided with the opportunity to undertake data analysis for a wide variety of statistical problems. You’ll build an appreciation of theoretical and practical perspectives on issues in medical statistics, whilst developing the ability to select and apply appropriate statistical methods for the analysis of medical data using suitably chosen software packages.
This course is taught by experts from the School of Mathematics, the Centre for Epidemiology and Biostatistics, and the Clinical Trials Research Unit at Leeds. You’ll study a mixture of modules taught by specialists in each area depending on your chosen optional modules. Teaching is done through a combination of lectures, small group workshops and a small number of practical exercises.
The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The project is assessed by a written dissertation and a short oral presentation.
There is a shortage of well-qualified statisticians in the UK and other countries. Numeracy, in general, is an attribute keenly sought after by employers.
The emergence of data mining and analysis means that demand for statisticians is growing across a wide range of professions - actuarial, betting and gaming industries, charitable organizations, commercial, environmental, financial, forensic and police investigation, government, market research, medical and pharmaceutical organisations. The course is designed specifically to meet this demand.
As a graduate of medical statistics you will have specialist knowledge that will help you progress your career into areas such as medical or epidemiological research. There are several aims to medical research, all of which involve a significant amount of statistics, monitoring and surveillance of health and disease, establishing causes of disease or factors associated with death or disease, detecting disease, preventing death or disease and evaluating treatments for disease. Medical statisticians looking to follow a career in medical research are mainly employed by pharmaceutical companies, university medical schools, research units and the NHS.
A medical statistician could also go into consultancy giving advice to researchers looking to set up clinical trials and needing their project to be assessed before funding is granted.
We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.
The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.
This programme is now closed but you may want to consider other courses such as the Mathematics MSc.
The Financial Mathematics MSc programme enables graduates and professionals with a strong mathematical background to research, develop and apply quantitative and computational techniques to investment and risk management. Based in the Department of Mathematics, this course has a superb reputation for research-led teaching and strong links to industry.
Financial Mathematics studies problems of optimal investment and risk management, and this course covers a diverse range of topics, from classical options pricing to post-crisis investment and risk management
Like any branch of applied mathematics, financial mathematics analyses a given problem by first building a mathematical model for it and then examining the model. Both steps require detailed knowledge in different areas of mathematics, including probability, statistics, optimisation, computer science and many more traditional fields of mathematics.
Our Financial Mathematics MSc course is a unique study pathway that encompasses the essential skills required for successful risk management, trading and research in quantitative finance: probability, statistics, optimisation, computing and financial markets. You will explore probability theories, risk neutral valuation, stochastic analysis as well as interest rate and credit risk modules. We also offer you the opportunity to study an additional zero-credit supportive module called mathematical analysis for financial mathematics.
The Financial Mathematics MSc programme offers you the choice to study either full or part-time and is made up of optional and required modules. You must take modules totalling 180 credits to complete the course. If you are studying full-time, you will complete the course in one year, from September to September. If you are studying part-time, your programme will take two years to complete, you will study the required modules in the first year, and a further selection of required and optional modules including the 60-credit financial mathematics report module in your second year.
Bloomberg terminal laboratory
King’s is one of only a few academic departments in the UK that offers full access to Bloomberg terminals. These terminals will provide you access to live financial data. They are heavily used within the financial industry, and the data they provide is critical in assisting traders in making investment decisions and for risk managers monitoring investment probabilities. We have 13 Bloomberg terminals available for exclusive use by the Financial Mathematics MSc programme.
You will use the Bloomberg terminals to:
The skills you will learn from using the terminals are highly valued by employers. King’s is part of a strong network of financial mathematics in London with connections both in academia and in the industry.
We are also members of the University of London and by arrangement, you can enrol in optional modules at other institutions within the University of London, which includes Birkbeck, London School of Economics and Political Sciences, University College London and many others.
This programme is suitable for students or professionals with a strong mathematical background. It covers the principles and techniques of quantitative finance to prepare students for advanced work in the financial sector or research in mathematical finance.
We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.
Average per week: Three hours for 11 weeks per each 15 credit module.
You are expected to spend approximately 10 hours of effort for each credit (so for a typical module of 15 credits this means 150 hours of effort).
The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations.
Our graduates are highly sought after by investment banks, corporate risk management units, insurance companies, fund management institutions, financial regulatory bodies, brokerage firms, and trading companies. Recent employers of our graduates include, Capital Investment, Credit Suisse, European Bank for Reconstruction & Development, Fitch Ratings, HSBC and Morgan & Stanley. Some graduates have pursued research degrees in financial mathematics.