-18.gif "Masters Degrees at University College London")
The Applied Mathematics group in the School of Mathematics at the University of Manchester has a long-standing international reputation for its research. Expertise in the group encompasses a broad range of topics, including Continuum Mechanics, Analysis & Dynamical Systems, Industrial & Applied Mathematics, Inverse Problems, Mathematical Finance, and Numerical Analysis & Scientific Computing. The group has a strongly interdisciplinary research ethos, which it pursues in areas such as Mathematics in the Life Sciences, Uncertainty Quantification & Data Science, and within the Manchester Centre for Nonlinear Dynamics.
The Applied Mathematics group offers the MSc in Applied Mathematics as an entry point to graduate study. The MSc has two pathways, reflecting the existing strengths within the group in numerical analysis and in industrial mathematics. The MSc consists of five core modules (total 75 credits) covering the main areas of mathematical techniques, modelling and computing skills necessary to become a modern applied mathematician. Students then choose three options, chosen from specific pathways in numerical analysis and industrial modelling (total 45 credits). Finally, a dissertation (60 credits) is undertaken with supervision from a member of staff in the applied mathematics group with the possibility of co-supervision with an industrial sponsor.
The course aims to develop core skills in applied mathematics and allows students to specialise in industrial modelling or numerical analysis, in preparation for study towards a PhD or a career using mathematics within industry. An important element is the course regarding transferable skills which will link with academics and employers to deliver important skills for a successful transition to a research career or the industrial workplace.
The course features a transferable skills module, with guest lectures from industrial partners. Some dissertation projects and short internships will also be available with industry.
Students take eight taught modules and write a dissertation. The taught modules feature a variety of teaching methods, including lectures, coursework, and computing and modelling projects (both individually and in groups). The modules on Scientific Computing and Transferable Skills particularly involve significant project work. Modules are examined through both coursework and examinations.
Assessment comprises course work, exams in January and May, followed by a dissertation carried out and written up between June and September. The dissertation counts for 60 credits of the 180 credits and is chosen from a range of available projects, including projects suggested by industrial partners.
Course unit details
CORE (75 credits)
* Introduction to Uncertainty Quantification
* Mathematical Methods
* Partial Differential Equations
* Scientific Computing
* Transferable Skills for Applied Mathematicians
OPTIONAL (3 modules, 45 credits)
* Applied Dynamical Systems (IM)
* Continuum Mechanics (IM)
* Stability theory (IM)
* Transport Phenomena and Conservation Laws (IM)
* Advanced Uncertainty Quantification (IM,NA)
* Approximation Theory and Finite Element Analysis (NA)
* Numerical Linear Algebra (NA)
* Numerical Optimization and Inverse Problems (NA)
Students registered on the Numerical Analysis pathway must select modules marked NA, and those registered on the Industrial Modelling pathway must select modules marked IM.
Syllabuses for the modules Introduction to Uncertainty Quantification and Advanced Uncertainty Quantification are currently being finalized and details will be added here as soon as possible.
Modern computing facilities are available to support the course.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The programme will prepare students for a career in research (via entry into a PhD programme) or direct entry into industry. Possible subsequent PhD programmes would be those in mathematics, computer science, or one of the many science and engineering disciplines where applied mathematics is crucial. The programme develops many computational, analytical, and modelling skills, which are valued by a wide range of employers. Specialist skills in scientific computing are valued in the science, engineering, and financial sector.
This one-year master's course provides training in the application of mathematics to a wide range of problems in science and technology. Emphasis is placed on the formulation of problems, on the analytical and numerical techniques for a solution and the computation of useful results.
By the end of the course students should be able to formulate a well posed problem in mathematical terms from a possibly sketchy verbal description, carry out appropriate mathematical analysis, select or develop an appropriate numerical method, write a computer program which gives sensible answers to the problem, and present and interpret these results for a possible client. Particular emphasis is placed on the need for all these parts in the problem solving process, and on the fact that they frequently interact and cannot be carried out sequentially.
The course consists of both taught courses and a dissertation. To complete the course you must complete 13 units.
There are four core courses which you must complete (one unit each), which each usually consist of 24 lectures, classes and an examination. There is one course on mathematical methods and one on numerical analysis in both Michaelmas term and Hilary term. Each course is assessed by written examination in Week 0 of the following term.
Additionally, you must choose at least least one special topic in the area of modelling and one in computation (one unit each). There are around twenty special topics to choose from, spread over all three academic terms, each usually consisting for 12 to 16 lectures and a mini project, which culminates in a written report of around 20 pages. Topics covered include mathematical biology, fluid mechanics, perturbation methods, numerical solution of differential equations and scientific programming.
You must also undertake at least one case study in modelling and one in scientific computing (one unit each), normally consisting of four weeks of group work, an oral presentation and a report delivered in Hilary term.
There is also a dissertation (four units) of around 50 pages, which does not necessarily need to represent original ideas. Since there is another MSc focussed on mathematical finance specifically, the MSc in Mathematical and Computational Finance, you are not permitted to undertake a dissertation in this field.
You will normally accumulate four units in core courses, three units in special topics, two units in case studies and four units in the dissertation. In addition, you will usually attend classes in mathematical modelling, practical numerical analysis and additional skills during Michaelmas term.
In the first term, students should expect their weekly schedule to consist of around seven hours of core course lectures and seven hours of modelling, practical numerical analysis and additional skills classes, then a further two hours of lectures for each special topic course followed. In addition there are about three hours of problem solving classes to go through core course exercises and students should expect to spend time working through the exercises then submitting them for marking prior to the class. There are slightly fewer contact hours in the second term, but students will spend more time working in groups on the case studies.
In the third term there are some special topic courses, including one week intensive computing courses, but the expectation is that students will spend most of the third term and long vacation working on their dissertations. During this time, students should expect to work hours that are equivalent to full-time working hours, although extra hours may occasionally be needed. Students are expected to write special topic and case study reports during the Christmas and Easter vacations, as well as revising for the core course written examinations.
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Mathematics and Computing for Finance at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
The MSc Mathematics and Computing for Finance course has been designed to meet the growing demand for specially trained mathematicians to work in the world’s financial markets and insurance.
Despite the current volatile nature of the banking industry, many banks still have a pressing need for employees with advanced mathematical skills who can further their understanding of turbulence in financial markets.
On the Mathematics and Computing for Finance course you will study different elements of both mathematics and computing in addition to developing your communication and presentational skills through a project you will undertake. As a student of the MSc in Mathematics and Computing for Finance programme you will be fully supported to ensure that your project is best suited to support your future career plans.
Have in depth knowledge in stochastic analysis and parts of advanced real analysis. (Fourier analysis and Partial Differential Equations) as well as parts of numerical analysis which are central for applications to finance.
Have developed advanced computing skills being essential for handling problems relevant for a job on the finance markets.
Have, as a mathematician, a good understanding of finance markets.
Have developed skills needed to work in a highly inter-disciplinary profession, including advanced programming techniques and communication skills across the borders.
Please visit our website for a full description of modules for the MSc Mathematics and Computing for Finance.
The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistically analysis, marketing and sales.
Some of our students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where maths graduates will find plenty of career opportunities.
The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.
All academic staff in Mathematics are active researchers and the department has a thriving research culture.
"Further to my studies at Swansea University as a Master of Science graduate in Financial Mathematics, I am currently working at Deutsche Bank in London as part of the Structured Financial Services team providing client services for corporate lending and debt portfolios. The complex nature of the course has helped me become a logical decision maker and a highly skilled problem solver. These transferable skills are very useful in the world of Finance since the role is highly challenging working towards deadlines and structured transaction targets. My studies at Swansea University have also enriched me with leadership, motivational skills and have enhanced my communication skills. I work in a close team of 10 people within a large department which encourages a culture that strives towards learning and effective teamwork. I thoroughly enjoyed my time at Swansea University and cherish the many fond memories. I am so pleased to be expanding my horizon within a major financial centre."
Rhian Ivey, BSc Mathematics, MSc Mathematics and Computing for Finance
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Mathematics at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
The MSc Mathematics course has been designed for students who wish to build on their BSc, extending their range of mathematics expertise across a broader spread of topics, and demonstrating their literature research skills through an extended dissertation.
Such a qualification will mark graduates out as having a broader and deeper understanding of mathematics, and the skills required to pursue a significant project with a high level of independence, presenting their results in a written report. This will give MSc Mathematics graduates an edge in the ever more competitive jobs market.
On the Mathematics course you will study different elements of mathematics in a broad sense - including mathematical elements of computing if desired - in addition to developing your research, project management, and written communication skills through a project you will undertake. As a student of MSc in Mathematics, you will be fully supported to ensure that your project further develops an excellent foundation for your future career plans.
Modules on the MSc Mathematics include:
• Algebraic coding theory
• Biomathematics
• Black-Scholes theory
• Data science
• Differential geometry
• Fourier analysis
• Ito calculus
• Lie theory
• Numerical analysis
• Partial differential equations
• Stochastic processes
• Statistical mechanics
• Topology
Please visit our website for a full description of modules for the MSc Mathematics.
On top of the Mathematics modules you study, you will also complete a dissertation as part of your studies.
The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use. It is a popular venue for students to work independently on the regular example sheets set by their lecturers, and to discuss Mathematics together.
Our main university library, Information Services and Systems (ISS), contains a notably extensive collection of Mathematics books.
Mathematics students will benefit from the £31m Computational Foundry for computer and mathematical sciences which will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)
The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistically analysis, marketing and sales.
Some of our Mathematics students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where Mathematics graduates will find plenty of career opportunities.
The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.
All academic staff in Mathematics are active researchers and the department has a thriving research culture.
http://www.swansea.ac.uk/postgraduate/taught/science/mscmathematics/
"Further to my studies at Swansea University as a Master of Science graduate in Financial Mathematics, I am currently working at Deutsche Bank in London as part of the Structured Financial Services team providing client services for corporate lending and debt portfolios. The complex nature of the Mathematics course has helped me become a logical decision maker and a highly skilled problem solver. These transferable skills are very useful in the world of Finance since the role is highly challenging working towards deadlines and structured transaction targets. My studies at Swansea University have also enriched me with leadership, motivational skills and have enhanced my communication skills. I work in a close team of 10 people within a large department which encourages a culture that strives towards learning and effective teamwork. I thoroughly enjoyed my time at Swansea University and cherish the many fond memories. I am so pleased to be expanding my horizon within a major financial centre."
Rhian Ivey, BSc Mathematics, MSc Mathematics and Computing for Finance
Globally, financial tools, products and software are becoming increasingly complex and sophisticated. There's a demand for market-aware graduates who can demonstrate an understanding of mathematical models used in these products.
The MSc in Quantitative Finance – an innovative cross-faculty alliance between the Strathclyde Business School and the Faculty of Science – has been developed to address this need. The course has been designed so that students who have a strong aptitude for mathematics, statistics and computing but who have not studied these topics in detail in their first degree can learn the necessary skills to move into the financial industry.
This masters course will prepare you for a career in financial engineering and risk management. Careers include roles as a hedge fund manager or financial analyst.
You’ll gain:
The curriculum provides a balance between finance and mathematical theory, computer implementations of this theory, and practical skills and knowledge.
Core classes are undertaken in the first semester, and address themes such as principles of finance and quantitative methods for finance, as well as foundation classes in mathematics, statistics and computing science.
You may be able to undertake an industrial based MSc project. This takes place in the third semester of the course between June and September. The placement can be based in the UK or in another country and are typically paid internships.
The Department of Mathematics & Statistics has teaching rooms which provide you with access to modern teaching equipment and access to University computing laboratories with all necessary software available.
You'll also have access to a common room facility which gives you a modern and flexible area which can be used for individual and group study work and is also a relaxing social space.
Classes are delivered by a number of teaching methods:
Teaching is student-focused, with students encouraged to take responsibility for their own learning and development. Classes are supported by web-based materials.
The form of assessment varies from class to class. For most classes the assessment involves both coursework and examinations.
Our graduates have gone on to find careers with reputable companies such as Deloitte, PWC, Bank of Ireland and BlackRock to name a few.
Job titles include:
Financial tools, products and software are becoming increasingly complex and sophisticated and there's a need for the finance industry to self-regulate as it witnesses unprecedented growth. Market-aware finance graduates, who understand the mathematical models used to develop these products and their computer implementations will be much in demand by international organisations.
Drawing on expert academic input from three departments – Accounting & Finance, Mathematics & Statistics, and Computer & Information Sciences – this one-year programme has been developed to prepare participants for careers within areas such as financial engineering and risk management, and for highly quantitative roles, such as hedge fund managers and financial analysts.
We also work closely with the University's Careers Service. They offer advice and guidance on career planning and looking for and applying for jobs. In addition they administer and publicise graduate and work experience opportunities.
This programme reflects and benefits from the strong research activities of the Department of Mathematics.
The taught modules and dissertation topics are closely aligned with the interests of the Department’s four research groups:
During the first two semesters you will take a range of taught modules from an extensive list of options, followed by an extended research project conducted over the summer under the supervision of a member of the department, culminating in the writing of a dissertation.
This programme is studied full-time over one academic year. It consists of eight taught modules and a dissertation.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
Mathematics is not only central to science, technology and finance-related fields, but the logical insight, analytical skills and intellectual discipline gained from a mathematical education are highly sought after in a broad range of other areas such as law, business and management.
There is also a strong demand for new mathematics teachers to meet the ongoing shortage in schools.
As well as being designed to meet the needs of future employers, our MSc programme also provides a solid foundation from which to pursue further research in mathematics or one of the many areas to which mathematical ideas and techniques are applied.
Knowledge and understanding
Intellectual / cognitive skills
Professional practical skills
Key / transferable skills
We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
The part-time MSc in Mathematical Finance aims to develop your mathematical modelling, data analysis and computational skills as applied to finance, without the need to take time out of your career to study.
Incorporating concepts from applied and pure mathematics, statistics, computing and corporate finance, the course gives you a broad intellectual perspective and covers, from fundamentals to the latest research, the most important aspects of quantitative finance currently in use in the finance industry.
The course:
It is possible to exit the course early and be awarded the Postgraduate Diploma in Mathematical Finance, should work pressures intervene before it is possible to write a dissertation.
In order to complete the MSc each student must attend and be assessed on four core modules, three advanced modules and to submit a dissertation. Students are expected to take seven terms (28 months) to complete the course.
Modules are taught through a series of lectures, practical sessions, guided reading, guest lectures and course assignments.
The core modules cover the mathematical foundations of probability, statistics and partial differential equations, stochastic calculus and martingale theory, portfolio theory, the Black-Scholes model and extensions, numerical methods (finite differences and Monte Carlo), interest rate modelling, stochastic optimisation, exotic derivatives and stochastic volatility. MATLAB and Python are used as a practical computing languages.
Attendance at the four core modules is compulsory. For each module there is an assignment for which feedback and an indicative mark is given to assist you in improving your future performance. Assessment for these compulsory modules consists of two two-hour written examinations held in September of the first year.
Each of the advanced modules explores a key area in contemporary mathematical finance. The programme of advanced modules is published in July each year, and you will be asked to register your choice of three modules. Attendance at these three assessed modules is compulsory. Advanced modules will be assessed by short ‘special project’ reports, each submitted on a subject chosen by you that is covered in the module.
You will complete a dissertation on a topic chosen in consultation with your supervisor and the Course Director.
This course was developed and is run in conjunction with SAS, it will provide you with the knowledge and skills to effectively research, develop and apply business intelligence systems. These are computerised information systems which support an organisation in the decision making process. Many of the techniques used in this area are underpinned by predictive statistics and mathematical modelling. This course will emphasise the concepts and techniques of business intelligence systems and their application and development. You will have access to specialist computing laboratories including one suite reserved specifically for postgraduate students. Upon graduating you be well placed to take up more general management and business information systems development roles within industry, or to undertake academic researchin this field.
• Taught by SAS accredited teaching staff
you will be taught by experienced SAS accredited teaching staff providing you with expert knowledge and skills allowing you to work toward your SAS accreditation
• SAS endorsed course
enhance your employability and gain substantial knowledge and skills in SAS business intelligence software leading towards SAS data miner accreditation
• 50 years history of research and teaching in computing technology
benefit from our well established academic expertise and advance your skills in, and knowledge of, developing business intelligence systems and data mining solutions to business problems
• Gain an insight into real world solutions
attend guest lectures and seminars, which will give you a real understanding of the impact of their work
• Excellent graduate prospects
graduates have gone into roles such as BI/SQL developers, logistics data modeller’s and insight analysts at organisations including Cognisco, LLamasoft and Occam DM
First semester
• Fundamentals of Business
Intelligence Systems
• Data Warehouse Design and OLAP
• Research Methods
• Statistics
Second semester
• Data Mining
• Business Intelligence Systems
Application and Development
• Analytics Programming
Plus two from the following list:
• Management of Information Systems
• Human Factors in Systems Design
• Applied Computational Intelligence
• Artificial Neural Networks
Third semester
• Final Project
Teaching will normally be delivered through formal lectures, informal seminars, tutorials, workshops, discussions and e-learning packages. Assessment will usually be carried out through a combination of individual and group work, presentations, reports, projects and exams.
Compulsory taught modules give you the opportunity to gain the fundamental knowledge and practices required to apply, develop and research business intelligence systems, while optional modules provide you with chances to study particular aspects of system application and development in more depth.
The individual project module allows you to undertake research into an aspect of business intelligence systems that interests you, and/or to perform appropriate business intelligence development tasks in response to a given practical problem.
Full-time students will normally attend around 16 hours of timetabled taught sessions per week, and can expect to undertake around 24 further hours of self-directed independent study and research to support your assignments and dissertation.
This course was developed and is run in conjunction with SAS. SAS is the world's largest independent business analytics company. It provides an integrated set of software products and services to more than 45,000 customer sites in 118 countries. Across the globe, both the public and private sector use SAS software to assist in their efforts to compete and excel in a climate of unprecedented economic uncertainty and globalization.
To learn more about this course and DMU, visit our website:
Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx
Applying for a postgraduate course:
Funding for postgraduate students:
