University of Leeds, School of Mathematics

Introduction

University of Leeds, School of Mathematics one of the largest and most prestigious mathematics departments in the UK, with an international reputation for our teaching and research excellence.

We cover the areas of applied and pure mathematics, as well as statistics and financial mathematics where we have close teaching and research links with Leeds University Business School.

Our courses consist of both compulsory and optional modules which provide the opportunity to cover a range of mainstream and advanced topics and innovative methods, selected from the research interests of the School of Mathematics. The choice of modules is dependent on your background, and subject to the agreement of the Course Co-ordinator.

You will have access to first class facilities, including the University Library, with its extensive range of print and online publications

Our Masters courses are strongly linked to our research groups which means that you are taught by staff who are actively engaged in world-class research and cutting-edge professional practice.

Each of these courses provides a pathway to progress on to a wide range of appealing PhD topics and may be combined with a subsequent PhD programme (subject to entry requirements). Across statistics, pure and applied mathematics there is ample scope to pursue a varied range of research topics. Whether you are looking to pursue a research career in your chosen area of mathematics or to develop the skills which will allow you to excel in industries requiring strong mathematical skills our Masters courses will provide you with an excellent grounding.

This school offers programs in:
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Programs

This school also offers:

MSc

MSc Atmosphere-Ocean Dynamics

Campus Full time 12 months September 2017 United Kingdom Leeds

This course is designed for students from a mathematical background who wish to apply their skills to understanding the complex behaviour of Earth's atmosphere and oceans. [+]

This course is designed for students from a mathematical background who wish to apply their skills to understanding the complex behaviour of Earth's atmosphere and oceans. This is an exciting interdisciplinary subject, of increasing importance to a society facing climate change. Training is offered in both modern applied mathematics and atmosphere-ocean science, combining teaching resources from the School of Mathematics and the School of Earth and Environment. The latter are provided by members of the School’s Institute for Climate and Atmospheric Science, part of the National Centre for Atmospheric Science. Only a handful of UK universities are positioned to offer similar interdisciplinary training. Course Description The focus of the course is on analysing the equations of fluid dynamics and thermodynamics, via mathematical and numerical modelling. Topics are drawn from four broad areas: ◾Applied mathematics: asymptotic methods, fluid dynamics, mathematical theory of waves and stability of flows ◾Numerical methods and computing: discretization of ordinary and partial differential equations, algorithms for linear algebra, direct use of numerical weather and climate models ◾Atmospheric dynamics: structure of the atmosphere, dynamics of weather systems and atmospheric waves ◾Ocean dynamics: the large-scale ocean circulation, surface waves and tides Course Structure The course is made up of two parts: a set of taught modules, and a research project. Two-thirds of the course consists of taught modules involving lectures and some computer workshops. Beyond a compulsory core of atmosphere-ocean fluid dynamics, students may choose options to suit their interests from applied maths (e.g. wave and stability theory), atmosphere-ocean science (e.g. climate change processes, weather forecasting), numerical methods and scientific computation.The final third of the course consists of an intensive summer project, in which students conduct an in-depth investigation of a chosen subject related to the course. Example modules offered by the School of Mathematics: ◾Mathematical Methods ◾Numerical Methods ◾Geophysical Fluid Dynamics ◾Astrophysical Fluid Dynamics ◾Linear and Nonlinear Waves ◾Nonlinear Dynamics Example modules offered by the School of Earth and Environment: ◾Atmosphere and Ocean Dynamics ◾Atmosphere-Ocean Climate Change Processes ◾Dynamics of Weather Systems ◾Practical Weather Forecasting ◾Computational Fluid Dynamics Career Options Students will be prepared for postgraduate research in applied mathematics or atmosphere-ocean science, or employment in the environmental sector. However, given the interdisciplinary nature of the programme, graduates will have expertise and skills in a number of different areas, and should be attractive to wider range of employers. Entry Requirements An upper-second class (2.1) degree or equivalent in Mathematics, or in a physical science subject with a substantial mathematics component. Candidates whose first language is not English will require an appropriate English language qualification, such as: ◾IELTS with a minimum score of 6.5 (with not less than 6.0 in all components) ◾Internet Based TOEFL (iBT) of at least 92 overall with no less than 21 in listening, 21 in reading, 23 in speaking and 22 in writing ◾Pearson Test of English (PTE) academic score of 64 with at least 60 in all components. [-]

MSc Data Science and Analytics

Campus Full time 12 months

This course is highly flexible, and offers the opportunity to develop a range of skills, including analysing structured and unstructured data, analysing large datasets and critically evaluating results in context, through a combination of compulsory and optional modules. [+]

We are surrounded by data. The variety and amount we collect and store grows every day, from the simplest of retail transactions to the complex and intimate medical records of millions. Why do we store data? Where do we store it? How do we retrieve it? What do we use it for? There is an increasing demand for individuals who can manage and control the way data is used. These individuals require an understanding of computer science and mathematics as well as a range of sector specific skills which can be applied in a variety of business environments. The Data Science and Analytics MSc is a highly flexible course which offers the opportunity to develop a range of skills, including analysing structured and unstructured data, analysing large datasets and critically evaluating results in context, through a combination of compulsory and optional modules. By choosing appropriate modules you can follow specific pathways, in business management, healthcare or geographic information systems (GIS), which will allow you to tailor the programme to suit your background and needs. The course combines expertise from the Schools of Computing, Geography and Mathematics with that of Leeds University Business School and the Yorkshire Centre for Health Informatics. This collaboration allows you to benefit from a range of data science perspectives and applications, supporting you to tailor your learning to your career ambitions. Modules are available from each of these areas and in addition there are three new modules available in mathematics for students who are not from a mathematics/statistics background, while modules in computing will be suitable for students on this course who are not from a computer science background. The course will therefore expose students to different perspectives on data science, including the mathematical and computational underpinnings of the subject and practical understanding of application in a specific context. In particular, we anticipate many projects for the dissertation will span at least two units with joint supervision. As well as emphasizing the application nature of the course, the dissertation will feature strongly data elucidation, analysis, and interpretation of real-world problems. [-]

MSc Mathematics

Campus Full time Part time 12 months September 2017 United Kingdom Leeds + 1 more

The MSc Mathematics programme provides a solid training in mainstream mathematics and will give you an insight into modern developments in mathematics. [+]

The MSc Mathematics programme provides a solid training in mainstream mathematics and will give you an insight into modern developments in mathematics.

The course is ideal for those who wish to take their studies of mathematics beyond the BSc level, for interest or to develop future employment opportunities. It also provides an excellent preparation for research for an MPhil or PhD. At Leeds we have a range of research opportunities available and in some cases you can progress to a PhD on the basis of a specified performance in the MSc.

Course Description

This course is designed to build on existing mathematical skills and allow students from a wide range of backgrounds to both broaden and deepen their understanding of their chosen branch of mathematics. The course allows specialisation in areas of pure mathematics, applied mathematics or statistics and allows the flexibility to cover a range of areas or to concentrate on one specific area.... [-]


MSc Mathematics and Computer Science

Campus Full time 12 months September 2017 United Kingdom Leeds

This interdisciplinary Masters degree provides a broad background in some mainstream and modern aspects of mathematics and computer science. You will be introduced to sophisticated techniques at the forefront of both disciplines. [+]

This interdisciplinary Masters degree provides a broad background in some mainstream and modern aspects of mathematics and computer science. You will be introduced to sophisticated techniques at the forefront of both disciplines. The programme combines teaching and research from the School of Mathematics and the School of Computing. Based on the Schools’ complementary research strengths the programme follows two main strands: ◾Algorithms and complexity theory ◾Numerical methods and parallel computing Course Description It is expected that most students will specialise in one of two areas during the course, although this is not essential. The two strands are: Algorithms and complexity theory and connections to logic and combinatorics This concerns the efficiency of algorithms for solving computational problems, and identifies hierarchies of computational difficulty. This subject has applications in many areas, such as distributed computing, algorithmic tools to manage transport infrastructure, health informatics, artificial intelligence, and computational biology. Numerical methods and parallel computing Many problems, in mathematics, physics, astrophysics and biology cannot be solved using analytical techniques and require the application of numerical algorithms for progress. The development and optimisation of these algorithms coupled to the recent increase in computing power via the availability of massively parallel machines has led to great advances in many fields of computational mathematics. This subject has applications in many areas, such as combustion, lubrication, atmospheric dispersion, river and harbour flows, and many more. Course Structure You are required to study 180 credits in total made up from taught modules and a research project. You will need to choose 120 credits worth of optional modules which in general are taken from across the two strands, Algorithms and Complexity Theory and Numerical Methods and also either one of the following compulsory modules: ◾Dissertation in Mathematics ◾MSc Project These are each 60 credit modules, taken over the summer (semester three). You will be assigned a research supervisor. Some possible dissertation topics will be advised, but you can also suggest your own topic (subject to approval). Career Options Each of these areas offers many career options, and the MSc will provide both technical and transferrable skills, for example, conducting an extended and independent research project. It will also offer excellent preparation for doctoral research in these or related subjects. On completion of the degree students can progress onto a wide range of opportunities including: ◾PhD in Mathematics, or in Computer Science. ◾Careers in Computing and Industries which require algorithmic tools (transport infrastructure, health informatics, computational biology, artificial intelligence, companies developing the internet (e.g. search engines). ◾Many other careers (e.g. in Finance) where a mathematics background is valued. In collaboration with both industrial and academic partners, our research has resulted in computational techniques, and software, that has been widely applied. Our industry links are extensive and include companies such as Google, Yahoo, Akamai, Microsoft, and Tracsis, as well as the NHS. Entry requirements A first or upper second class (2.1) BSc degree in mathematics or computer science (with a substantial mathematics component), or equivalent. We will also consider students who hold other degrees with a substantial mathematics component. English Language Requirements A pass at GCSE level in English Language (grade C or above). Candidates whose first language is not English will require an appropriate English language qualification, such as: ◾IELTS with a minimum score of 6.5 (with not less than 6.0 in all components) ◾Internet Based TOEFL (iBT) of at least 92 overall with no less than 21 in listening, 21 in reading, 23 in speaking and 22 in writing ◾Pearson Test of English (PTE) academic score of 64 with at least 60 in all components. [-]

MSc Medical Statistics

Campus Full time Part time 12 - 24 months September 2017 United Kingdom Leeds + 1 more

A flexible taught masters course in statistics combining in-depth training in mainstream advanced statistical modelling with a specialisation in medical applications. [+]

A flexible taught masters course in statistics combining in-depth training in mainstream advanced statistical modelling with a specialisation in medical applications. The MSc in Medical Statistics is a flexible degree programme blending theoretical and applied statistical disciplines ideal for training in medical statistics. It combines compulsory and optional modules allowing students 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. Course description The course is available as a full-time MSc lasting 12 months or as a part-time option studied over 24 months, both starting in September. The programme provides training in a core of statistical techniques (and transferable skills) suitable for either careers in medical statistics or for further academic research. The Course consists of two semesters of taught modules, with the third semester devoted to a major dissertation or research project. Within each semester there is one compulsory module. However, students tailor the course to meet their individual needs through selection of a further three modules from a variety of options. Options within the course vary from mainstream topics in statistical methodology to more specialised areas such as epidemiology and biostatistics. Course structure 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, each bringing a different perspective to the subject of medical statistics. The programme combines taught modules with a summer project, supervised between the teaching units and utilising 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. The course covers modern developments in statistics and provides the opportunity to undertake data analysis for a wide variety of statistical problems. It aims to 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. Compulsory modules; ◾Introduction to Clinical Trials ◾Core Epidemiology ◾Introduction to Modelling ◾Statistical Computing Optional modules studied may include; ◾Advanced Epidemiology ◾Linear Regression and Robustness ◾Generalised Linear Models and Survival Analysis ◾Time Series and Spectral Analysis Career options 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 researcher looking to set up clinical trials and needing their project to be assessed before funding is granted. Entry requirements A minimum of a BSc upper second class (2.1) honours degree or equivalent is required, which includes mathematics and statistics. No background in medicine is required. Candidates whose first language is not English will require an appropriate English language qualification, such as; ◾IELTS (academic) 6.5 with at least 6.0 in all components ◾TOEFL score (internet-based test) of at least 92 overall with no less than 21 in listening, 21 in reading, 23 in speaking and 22 in writing ◾Pearson Test of English (PTE) academic score of 64 with at least 60 in all components. [-]

MSc Statistics

Campus Full time 12 months September 2017 United Kingdom Leeds

A flexible taught masters course in statistics combining in-depth training in mainstream advanced statistical modelling with a broad range of specialisations. [+]

This course is accredited by the Royal Statistical Society. A flexible taught masters course in statistics combining in-depth training in mainstream advanced statistical modelling with a broad range of specialisations - from financial mathematics to statistical bioinformatics; from shape analysis to risk management. The MSc in Statistics is a flexible degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics. It provides training in a range of statistical techniques (and transferable skills) suitable for either careers in statistics and research-related professions, or for further academic research in statistics. Course Description The course is a full-time MSc lasting 12 months, starting in September. The Course consists of two semesters of taught modules, with the third semester devoted to a major dissertation. Within each semester there is one compulsory module. However, students tailor the course to meet their individual needs through selection of a further three modules from a variety of options. This selection process means a student can specialise in biological or financial applications of statistics or retain a broad base of statistical expertise. Options within the course vary from mainstream topics in statistical methodology to more specialised areas and reflect specific research interests of academic staff - examples include statistical shape analysis, directional data, statistical genetics and stochastic financial modelling. Course Structure Semester One Statistical Computing (compulsory): An introduction to methods of statistical computing. Essential for the applied statistician, with an emphasis on sampling-based methods, such as Markov chain Monte Carlo. Optional modules include: ◾Multivariate and Cluster Analysis ◾Statistics and DNA ◾Linear Regression and Robustness and Smoothing ◾Stochastic Financial Modelling ◾Discrete Time Finance Semester Two Independent Learning Skills (compulsory): An introduction to research methods including literature search, writing styles, mathematical typesetting and programming skills. Optional modules include: ◾Statistical Theory ◾Times Series and Spectral Analysis ◾Shape Analysis and Directional Data ◾Continuous Time Finance ◾Risk Management ◾Hidden Markov Models for Biological Sequence Analysis Semester Three Dissertation in Statistics: A four-month research project undertaken in the Summer on a topic (chosen in conjunction with project supervisors) culminating in a dissertation on that project. Example Project Topics include: ◾Shape Analysis ◾Spatial Statistics ◾Robustness ◾Data Mining ◾Wavelets ◾Bioinformatics The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester three project is assessed by a written dissertation and a short oral presentation. Career Options 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. Many statistical careers require people educated to masters degree level. This course is designed to build on existing mathematical skills and deepen knowledge of statistics in order for you to access a variety of professions or pursue further research as a PhD student. The MSc is accredited by the Royal Statistical Society. Completion of the programme will qualify students for the status of ‘Graduate Statistician’ - the first stage towards Chartered Statistician status. Entry Requirements A minimum of a BSc upper second class (2.1) honours degree or equivalent is required, in a subject relevant to the programme of study. Candidates whose first language is not English will require an appropriate English language qualification, such as; ◾IELTS (academic) 6.5 with at least 6.0 in all components ◾TOEFL score (internet-based test) of at least 92 overall with no less than 21 in listening, 21 in reading, 23 in speaking and 22 in writing ◾Pearson Test of English (PTE) academic score of 64 with at least 60 in all components. [-]

MSc Statistics with Applications to Finance

Campus Full time 12 months September 2017 United Kingdom Leeds

The MSc in Statistics with Applications to Finance is a focussed degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics and financial applications. As well as the statistics expertise within the School of Mathematics, the MSc also draws on experience in Financial Mathematics, a joint venture between the School of Mathematics and Leeds University Business School headed by Professor Klaus Schenk-Hoppé. [+]

The MSc Statistics with Applications to Finance is a taught Masters course in statistics combining in-depth training in mainstream advanced statistical modelling with a specialisation in financial mathematics. It is a focussed degree programme enabling students from a wide range of backgrounds to both broaden and deepen their understanding of statistics and financial applications. As well as the statistics expertise within the School of Mathematics, the MSc also draws on experience in Financial Mathematics, a joint venture between the School of Mathematics and Leeds University Business School headed by Professor Klaus Schenk-Hoppé.

Course Description

The programme provides training in a core of statistical techniques (and transferable skills) suitable for either careers in statistical finance or for further academic research. The course is a full-time MSc lasting 12 months, starting in September. The Diploma is just over 8 months duration. The Course consists of two semesters of taught modules, with the third semester devoted to a major dissertation. Within each semester there are three compulsory modules. However, students tailor the course to meet their individual needs through selection of a further module in each semester from a variety of options.... [-]