Masters Degrees in Stochastic Processes, United Kingdom

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Stochastic Processes: Theory and Application at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

The MRes in Stochastic Processes: Theory and Application is delivered through optional modules for the taught element followed by a large research project that contributes to the field in an explicit way, rather than merely applying existing knowledge.

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

The Department’s research groups include:

Algebra and Topology Group

Areas of interest include: Noncommutative geometry, Categorical methods in algebra and topology, Homotopy theory and homological algebra and others.

Analysis and Nonlinear Partial Differential Equations Group

Areas of interest include: Reaction-diffusion and reaction-diffusion-convection equations and systems, Navier–Stokes equations in fluid dynamic, Complexity in the calculus of variations and others.

Stochastic Analysis Group

Areas of interest include: Functional inequalities and applications, Lévy-type processes, Stochastic modelling of fractal, multi-fractal and multi-scale systems, Infinite dimensional stochastic analysis and others.

Mathematical Methods in Biology and Life Sciences Group

Areas of interest include: Mathematical pharmacology; heat and mass transfer models for plant cooling; modelling cellular signal transduction dynamics; mathematical oncology: multi-scale modelling of cancer growth, progression and therapies, and modelling-optimized delivery of multi-modality therapies; multi-scale analysis of individual-based models; spreading speeds and travelling waves in ecology; high performance computing.

Key Features

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

Course Content

As a student on the MRes Stochastic Processes programme you will study a range of topics for the taught element including:

Stochastic Calculus based on Brownian Motion

Levy processes and more general jump processes

The advanced Black-Scholes theory

Theory and numerics of parabolic differential equations

Java programming

The Stochastic Processes: Theory and Application course consists of a taught part (60 credits) and a research project (120 credits). Students will have a personal supervisor for their research project from the start of their studies.

Research projects could be of a theoretical mathematical nature, or they could be more applied, for example in financial mathematics or actuarial studies. Some of the research projects will be of an interdisciplinary character in collaboration with some of Swansea's world class engineers. For such projects it is likely that EPSRC funding would be available.

Facilities

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.

Careers

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, statistical 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.

Research

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.

Read less

About the MSc programme

The MSc Financial Mathematics is based in the Department of Mathematics, and is taught in collaboration with the Department of Finance and the Department of Statistics. The programme draws on LSE's strengths in finance and related areas to provide high-level instruction in the mathematical theory underlying finance, and training in appropriate computational methods.

The programme aims to develop your understanding of quantitative methodologies and techniques which are important for a range of jobs in investment banks and other financial institutions; to enhance your critical appreciation of major issues and emerging theory in the area of financial mathematics; and to improve your personal skills, including logical reasoning, quantitative analysis and the presentation of technical results.

In addition to compulsory courses in The Mathematics of the Black and Scholes Theory, The Foundations of Interests Rate and Credit Risk Theory, Stochastic Processes, Fixed Income Markets, and Computational Methods in Finance, you will choose optional courses to the value of one and a half units. Choices include stochastic analysis, preferences, optimal portfolio choice, equilibrium, derivatives modelling, Markov processes, financial risk analysis, international finance, and forecasting of financial time series.

Graduate destinations

This programme is ideal preparation for a range of careers in the financial sector, industry and research.

Read less

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).

As an MSc by Research in Mathematics student you will be guided by internationally leading researchers and will carry out a large individual research project.

You will be fully integrated into one of our established research groups and participate in research activities such as seminars, workshops, laboratories, and field work.

Key Features

Swansea is a research-led University and the Mathematics Department makes a significant contribution, meaning that as a postgraduate Mathematics student you will benefit from the knowledge and skills of internationally renowned academics.

In the Department of Mathematics at Swansea you will find friendly teaching staff that are fully committed to providing you with a supportive teaching and learning environment. This includes outstanding student support.

All postgraduate Mathematics programmes at Swansea will equip you with skills relevant for a rewarding career in a range of diverse fields. You will also further develop your communication, presentation and analytical skills.

The Mathematics Department’s research groups include:

Algebra and Topology Group

Areas of interest include: Noncommutative geometry, Categorical methods in algebra and topology, Homotopy theory and homological algebra and others.

Analysis and Nonlinear Partial Differential Equations Group

Areas of interest include: Reaction-diffusion and reaction-diffusion-convection equations and systems, Navier–Stokes equations in fluid dynamic, Complexity in the calculus of variations and others.

Stochastic Analysis Group

Areas of interest include: Functional inequalities and applications, Lévy-type processes, Stochastic modelling of fractal, multifractal and multiscale systems, Infinite dimensional stochastic analysis and others.

Mathematical Methods in Biology and Life Sciences Group

Areas of interest include: Mathematical pharmacology; heat and mass transfer models for plant cooling; modelling cellular signal transduction dynamics; mathematical oncology: multi-scale modelling of cancer growth, progression and therapies, and modelling-optimized delivery of multi-modality therapies; multi-scale analysis of individual-based models; spreading speeds and travelling waves in ecology; high performance computing

Employability

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, statistical analysis, marketing and sales.

Facilities

The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use, and is a popular venue for students to work independently on the regular exercise sheets set by their lecturers, and to discuss mathematics together.

The main university library, the Learning and Information Centre (LIC), contains a notably extensive collection of mathematics books.

As part of our expansion, we are building the Computational Foundry on our Bay Campus for computer and mathematical sciences. This development is exciting news for Swansea Mathematics who are part of the vibrant and growing community of world-class research leaders drawn from computer and mathematical sciences.

Research

The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Mathematics 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.

Read less

Mathematical Biology at Dundee

The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. In his famous book On Growth and Form (where he applied geometric principles to morphological problems) Thompson declares:

"Cell and tissue, shell and bone, leaf and flower, are so many portions of matter, and it is in obedience to the laws of physics that their particles have been moved, molded and conformed. They are no exceptions to the rule that God always geometrizes. Their problems of form are in the first instance mathematical problems, their problems of growth are essentially physical problems, and the morphologist is, ipso facto, a student of physical science."

Current mathematical biology research in Dundee continues in the spirit of D'Arcy Thompson with the application of modern applied mathematics and computational modelling to a range of biological processes involving many different but inter-connected phenomena that occur at different spatial and temporal scales. Specific areas of application are to cancer growth and treatment, ecological models, fungal growth and biofilms. The overall common theme of all the mathematical biology research may be termed"multi-scale mathematical modelling" or, from a biological perspective, "quantitative systems biology" or"quantitative integrative biology".

The Mathematical Biology Research Group currently consists of Professor Mark Chaplain, Dr. Fordyce Davidson and Dr. Paul Macklin along with post-doctoral research assistants and PhD students. Professor Ping Lin provides expertise in the area of computational numerical analysis. The group will shortly be augmented by the arrival of a new Chair in Mathematical Biology (a joint Mathematics/Life Sciences appointment).

As a result, the students will benefit directly not only from the scientific expertise of the above internationally recognized researchers, but also through a wide-range of research activities such as journal clubs and research seminars.

Aims of the programme

1. To provide a Masters-level postgraduate education in the knowledge, skills and understanding of mathematical biology.
2. To enhance analytical and critical abilities and competence in the application of mathematical modeling techniques to problems in biomedicine.

Prramme Content

This one year course involves taking four taught modules in semester 1 (September-December), followed by a further 4 taught modules in semester 2 (January-May), and undertaking a project over the Summer (May-August).

A typical selection of taught modules would be:

Dynamical Systems
Computational Modelling
Statistics & Stochastic Models
Inverse Problems
Mathematical Oncology
Mathematical Ecology & Epidemiology
Mathematical Physiology
Personal Transferable Skills

Finally, all students will undertake a Personal Research Project under the supervision of a member of staff in the Mathematical Biology Research Group.

Methods of Teaching

The programme will involve a variety of teaching formats including lectures, tutorials, seminars, journal clubs, case studies, coursework, and an individual research project.

Taught sessions will be supported by individual reading and study.

Students will be guided to prepare their research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

Career Prospects

The Biomedical Sciences are now recognizing the need for quantitative, predictive approaches to their traditional qualitative subject areas. Healthcare and Biotechnology are still fast-growing industries in UK, Europe and Worldwide. New start-up companies and large-scale government investment are also opening up employment prospects in emerging economies such as Singapore, China and India.

Students graduating from this programme would be very well placed to take advantage of these global opportunities.

Read less

The MSc Financial Mathematics draws on tools from applied mathematics, computer science, statistics and economic theory to prepare you for roles in which you will combine in-depth knowledge of financial products and risk with sophisticated technical and programming skills.

You will acquire solid knowledge of probability theory and stochastic processes, numerical analysis and programming languages, asset pricing theory and risk analysis, with special emphasis on valuation and risk management.

Typical career paths of graduates from our MSc Financial Mathematics include research positions (in both financial and academic institutions), or roles involving the development, management and improvement of derivatives models using advanced programming languages, and model validation such as Equity/Equity Derivatives Quant, Quantitative Financial Engineer, or Quantitative Risk Analyst.

This programme is rigorous with respect to the mathematics but also places great emphasis on linking theory with real world developments. You will often be exposed to the teaching of real world practitioners from the City of London.

Cass's proximity to the City of London, and our close links to many of its institutions, will help you to access outstanding networking and career opportunities.

Visit the website: http://www.cass.city.ac.uk/courses/masters/courses/financial-mathematics

Course detail

There are two Induction Weeks The Financial Mathematics course starts with two compulsory induction weeks, focused on:

• an introduction to careers in finance and the opportunity to speak to representatives from over 75 companies during a number of different industry specific fairs.

• a reminder course of advanced financial mathematics, statistics and basic computing which forms a prerequisite of the core modules in term 1.

Attendance is mandatory.

Format

To satisfy the requirements of the degree course students must complete:

• eight core courses (15 credits each)
and
• two additional core modules plus three electives (10 credits each)
or
• three electives (10 credits each) and an Applied Research Project (20 credits)
or
• one elective (10 credits) and a Business Research Project (40 credits)

Assessment

Assessment of modules on the MSc in Financial Mathematics, in most cases, is by means of coursework and unseen examination. Coursework may consist of standard essays, individual and group presentations, group reports, classwork, unseen tests and problem sets. Please note that any group work may include an element of peer assessment.

Career opportunities

Many graduates from the MSc in Financial Mathematics progress to one of two fields:

• derivatives valuation and portfolio management within investment houses
• research departments within banks and consultancy firms

Some examples of where graduates from the MSc in Financial Mathematics class of 2014 are working are:

• Bank of China - Management Trainee
• Santander - Credit Fraud Analyst
• Renaissance Re - Analyst
• Deutsche Bank - Bookrunner

How to apply

Apply here: http://www.city.ac.uk/study/postgraduate/applying-to-city

Funding

For information on funding, please follow this link: http://www.city.ac.uk/study/postgraduate/funding-and-financial-support

Read less

Overview

Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering.
By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied.

Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications.

Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved.

Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise?

This course is one of a suite of MScs in Scientific Computation that are genuinely multidisciplinary in nature. These courses are taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry.

Key facts:
- This course is offered in collaboration with the School of Computer Science.
- It is one of a suite of courses focusing on scientific computation.
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.
- In the latest independent Research Assessment Exercise, the school ranked 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).

Modules

Advanced Techniques for Differential Equations

Computational Linear Algebra

Operations Research and Modelling

Programming for Scientific Computation

Scientific Computation Dissertation

Simulation for Computer Scientists

Stochastic Financial Modelling

Variational Methods

Vocational Mathematics

Data Mining Techniques and Applications

Mathematical Foundations of Programming

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information

Read less

About the course

Graduates with skills in these areas are in demand. The course is about applying probabilistic, statistical and mathematical techniques in the finance industry. It’s based on the MSc Statistics with additional training in the concepts, models and tools of modern mathematical finance. This course is accredited by the Royal Statistical Society.

Your career

Our graduates go into finance, manufacturing and pharmaceuticals. They work for government agencies and research institutes with major organisations such as First Direct, GlaxoSmithKline, Marks and Spencer, the Government Statistical Service and Medical Research Council units. Our courses can also prepare you for PhD-level research.

About us

Our academics are in demand. They are members of international societies and organisations, and they speak at conferences around the world. They bring new ideas into the classroom so you can see how research is improving on existing approaches. Our solar scientists were the first to record musical sounds created by vibrations in the sun’s atmosphere.

Our Statistical Services Unit works with industry, commerce and the public sector. The services they provide include consultancy, training courses and computer software development.

Different ways to study

You can study full-time over a year or part-time over two to three years via online distance learning. The MSc Mathematics is only available as a full-time course.

Studentships

You may be able to get funding from the University or an external company. Course-specific studentships may also be available. You should apply for these as soon as possible.

Core modules

Data Analysis; Statistical Laboratory; Linear Models; Inference; Financial Mathematical, Dependent Data; Stochastic Processes and Finance.

Teaching and assessment

There are lectures, tutorials and computing sessions. You’ll do group work, presentations and role play. Most statistics lectures are recorded so you can watch them again later.

The distance learning option is taught online with support via email and phone. Distance learners also come to the University for residential weeks. You’re assessed by exams, project work and a dissertation.

Read less

About the course

This intensive introduction to advanced pure and applied mathematics draws on our strengths in algebra, geometry, topology, number theory, fluid dynamics and solar physics. You’ll attend lectures but you’ll also get hands-on research experience, writing a dissertation supervised by an active researcher.

Your career

Our graduates go into finance, manufacturing and pharmaceuticals. They work for government agencies and research institutes with major organisations such as First Direct, GlaxoSmithKline, Marks and Spencer, the Government Statistical Service and Medical Research Council units. Our courses can also prepare you for PhD-level research.

About us

Our academics are in demand. They are members of international societies and organisations, and they speak at conferences around the world. They bring new ideas into the classroom so you can see how research is improving on existing approaches. Our solar scientists were the first to record musical sounds created by vibrations in the sun’s atmosphere.

Our Statistical Services Unit works with industry, commerce and the public sector. The services they provide include consultancy, training courses and computer software development.

Different ways to study

You can study full-time over a year or part-time over two to three years via online distance learning. The MSc Mathematics is only available as a full-time course.

Modules

Possible module choices include: Algebra; Analysis; Geometry; Algebraic Topology; Number Theory; Topics in Advanced Fluid Dynamics; Analytical Dynamics and Classical Field Theory; Mathematical Modelling of Natural Systems; Stochastic Processes and Finance; Waves and Magnetohydrodynamics.

Teaching and assessment

There are lectures and seminars. You’re assessed by exams, coursework and a dissertation.

Read less

The financial services industry place great emphasis on raising the level of mathematics used in banks in applications to pricing, hedging and risk management. This MSc provides students with the skills necessary in mathematics, statistics and computation for a career in this fast-developing field.

Degree information

Students will develop a detailed understanding of the application of mathematics, statistics and computation to problems in finance, and will gain the necessary practical tools for the pricing, hedging and risk management of a diverse range of financial products in several asset classes.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits) four optional modules (60 credits) and a research dissertation (60 credits).

A Postgraduate Diploma will be offered to the students that have completed 8 taught modules (120 UCL credits).A Postgraduate Certificate will be offered to the students that have completed 4 taught modules (60 UCL credits).

Core modules
-Asset Pricing in Continuous Time
-Forecasting
-Interest Rates and Credit Modelling
-Quantitative and Computational Finance

Optional modules - four modules must be chosen from the following list:
-Applied Computational Finance
-Equities, Foreign Exchange and Commodities Modelling
-Market Risk, Measures and Portfolio Theory
-Mathematics and Statistics of Algorithmic Trading
-Numerical Analysis for Finance
-Probability
-Statistical Inference
-Stochastic Processes
-Quantitative Modelling of Operational Risk and Insurance Analytics

Dissertation/report
All MSc students undertake an independent research project, which culminates in a research report of approximately 10,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, practical classes, tutorials and problem-solving exercises. Assessment is through written papers, coursework, examinations and the research report and presentation.

Careers

Many students have progressed to careers in financial services in the City of London or in their home country; a number of graduates have proceeded to a PhD.

Top career destinations for this degree:
-University Teacher, Chechen State University
-Operational Permanent Control Analyst, BNP Paribas
-UK Education Consultant, SI-UK Education Council
-CFA (Chartered Financial Analyst), Quartic Training
-MSc Financial Mathematics, University College London (UCL)

Employability
The financial services industry requires quantitative finance professionals who are able to analyse data, to program, and who are expert in mathematics and computational statistics. Career prospects for graduates of this programme are excellent.

Why study this degree at UCL?

UCL Mathematics is an internationally renowned department which carries out excellent individual and group research applying modelling techniques to problems in financial, 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.

A notable aspect of this applied Master's programme is that students will be educated to an advanced level in statistics and computing.

Read less

Our MPhil/PhD degree in Mathematics and Statistics aims to train you to conduct research of a high academic standard and to make original contributions to the subject.

The programme involves coursework (where suitable) and research training, but its major component is the preparation of a substantial research thesis. The thesis should demonstrate a sound understanding of the main issues in the area and add to existing knowledge.

Research interests in mathematics and statistics include: mathematical finance, in particular the analysis of risk and numerical computation; mathematical physics and partial differential equations; approximation theory and numerical analysis; probability and stochastic processes, pure and applied; applied statistics and multivariate analysis; covariance modelling for repeated measures and longitudinal data; medical statistics; combinatorics, algebra and designs.

Our research

Birkbeck is one of the world’s leading research-intensive institutions. Our cutting-edge scholarship informs public policy, achieves scientific advances, supports the economy, promotes culture and the arts, and makes a positive difference to society.

Birkbeck’s research excellence was confirmed in the 2014 Research Excellence Framework, which placed Birkbeck 30th in the UK for research, with 73% of our research rated world-leading or internationally excellent.

Read less

Computational mathematics is relevant to almost every science, engineering, business and finance discipline, as well as many industrial sectors. This means it’s an excellent choice if you’re considering broadening your career options whilst studying a discipline that is in high demand in an ever technological era. Studying this MSc is also excellent preparation for academic research in any area where computational techniques play a significant role, offering you a clear route to further study at PhD level.

The course delivers an outstanding combination of advanced applicationoriented mathematical concepts and computational methodologies. Broad in scope and genuinely multidisciplinary in nature, it’s based on solid and well-founded mathematical theory.

Subject modules are carefully designed to be accessible to anyone with a good first degree in mathematics or in science and engineering subjects which have a strong mathematical component.

Here at the University of Derby, our teaching team has wide-ranging expertise in contemporary areas of mathematics and their applications to modern society. You’ll be inspired by academics and practitioners who have experience of harnessing mathematics and computing to address real-world problems.

You’ll benefit from flexible study options to fit in with your lifestyle. If you’re already in employment, you can gain this MSc through part time study while developing your knowledge and technical competence in ways that are directly relevant to your job.

You’ll study modules such as:

Optimisation
Scientific Computing
Stochastic Processes
Networks and Algorithms
Nonlinear System Dynamics
Studying at Masters Level and Research Methods
Independent Scholarship

Read less

The financial sector is increasingly using sophisticated mathematical models to predict the development of markets and risks related to the services and products it provides. Banks, building societies, accountancy, insurance, investment and pension companies demand graduates with strong quantitative skills. This programme aims to prepare you for a successful career in these fields.

Taught by Mathematics at the School of Science and Engineering and Business at the School of Social Sciences, we ensure you can experience both the mathematical and economic perspective of the subject.

Why study this course at Dundee?

This courses offers a challenging range of modules across disciplines at the University of Dundee, one of the highest ranked universities in in UK for student experience and satisfaction.

Mathematics is central to many disciplines across a wide variety of fields particularly in the financial sector. You will enhance your analytical and critical abilities and competence in the application of mathematics to solve real world problems.

Demand for people with mathematical qualifications in the financial sector is particularly high and graduates of this programme will gain a significant advantage to further their career within the financial industry.

What's so good about this course at Dundee?

Mathematics at the University of Dundee consistently enjoys high rankings in student satisfaction and experience. It was ranked second in Scotland, and sixth in the UK by The Times & Sunday Times Good University Guide 2016.

The University has an international reputation for world class teaching and research. Mathematics at the University of Dundee was ranked top in Scotland and eighth in the UK for the quality and impact of its research.

You will be taught by staff who have experience applying mathematical models to financial problems or who have gained insight into the financial sector through practical experience or research.

The MSc Mathematics for the Financial Sector is a highly marketable qualification which will prepare you for a successful and rewarding career.

Teaching & Assessment

- How you will be taught

You'll learn by traditional methods such as lectures, tutorials, and workshops as well as via computer assisted learning. We also teach the use of professional mathematical/statistical/financial software packages in order to allow students to explore more complex problems and as a preparation for their future employment.

Individual reading and study takes a particularly important role in the summer project. For the project, we will guide you with preparation of your research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

- How you will be assessed

About 50% of the assessments are written (formal) examinations, 35% are coursework/continuous assessment and the remaining 15% is the project report.

What you will study

The course comprises the following modules in Semester 1 and 2:

Compulsory

Dynamical Systems (15 credits)
Stochastic Processes (15 credits)
Global Financial Markets, (20 credits)
Optimisation in Finance and Energy (15 credits)
Derivatives & Risk Management (20 credits)

Advised

Computational Modelling (15 credits)
Econometrics for Finance, (20 credits)
Inverse Problems (15 credits)
Global Risk Analysis (20 credits)
This is complemented with a project (25 credits) over the summer, which may take the form of either a review-based analysis of applications of mathematics to the financial sector or a report based on work experience gained in the financial sector.

Non-compulsory modules of up to 30 credits can be replaced with other comparable modules such as Introduction to Data Mining and Machine Learning or Programming Languages for Data Engineering.

Employability

Employers value the precision and reasoning of mathematics graduate which makes them some of the most high-sought and highly paid graduate in the UK. This programme will equip you with analytical and decision tools required for careers in fields such as finance, banking and business.

This programme is designed distinguish our graduates from an increasingly large graduate population within these sectors.

Read less

This masters is run jointly with Heriot-Watt University. It provides you with expertise in financial mathematics, including stochastic calculus, and a range of practical techniques for analysing financial markets. You will also learn quantitative skills for developing and managing risk that are in high demand since the recent financial crisis.

Adding depth to your learning, our work placement programme puts you at the heart of organisations such as Aberdeen Asset Management, Moody’s Analytics and Lloyds Banking Group.

Programme structure

This programme involves two taught semesters of compulsory and option courses, followed by a dissertation project.

Compulsory courses:

• Credit Risk Modelling
• Derivatives Markets
• Derivative Pricing and Financial Modelling
• Discrete-Time Finance
• Financial Markets
• Special Topics 1
• Special Topics 2
• Stochastic Analysis in Finance

Option courses:

• Deterministic Optimization Methods in Finance
• Financial Econometrics
• Portfolio Theory
• Numerical Techniques of Partial Differential Equations
• Optimization Methods in Finance
• Simulation
• Statistical Methods
• Statistical Inference
• Time Series Analysis
• Stochastic Control and Dynamic Asset Allocation

Career opportunities

Graduates typically work in major financial institutions or continue their studies by joining PhD programmes.

Read less

Applied Mathematical Sciences offers a clear and relevant gateway into a successful career in business, education or scientific research. The programme arms students with the essential knowledge required by all professional mathematicians working across many disciplines. You will learn to communicate their ideas effectively to peers and others, as well as the importance of research, planning and self-motivation.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

:

Modelling and Tools;
Optimization;
Dynamical Systems;
Applied Mathematics (recommended);
Applied Linear Algebra (recommended).

Optional Courses

:

Mathematical Ecology;
Functional Analysis;
Numerical Analysis of ODEs;
Pure Mathematics;
Statistical Methods;
Stochastic Simulation;
Software Engineering Foundations;
Mathematical Biology and Medicine;
Partial Differential Equations;
Numerical Analysis;
Geometry.

Typical project subjects

:

Pattern Formation of Whole Ecosystems;
Climate Change Impact;
Modelling Invasive Tumour Growth;
Simulation of Granular Flow and Growing Sandpiles;
Finite Element Discretisation of ODEs and PDEs;
Domain Decomposition;
Mathematical Modelling of Crime;
The Geometry of Point Particles;
Can we Trust Eigenvalues on a Computer?

Read less

This masters programme covers the advanced mathematics that has revolutionised finance since the works of Black, Scholes and Merton in the early seventies. This programme is aimed at those students who are passionate about mathematics and driven to make a career amongst the many and varied financial institutions throughout the world.

The programme, which is part of the Maxwell Institute for Mathematical Sciences, the joint research institute of mathematical sciences at the University of Edinburgh and Heriot-Watt University, provides an intensive training in the mathematical ideas and tools vital to the finance industry. By developing essential new mathematical concepts, especially in stochastic calculus, and placing the mathematics in the contexts of financial markets, derivative pricing and credit risk, the programme equips students for a range of exciting and potentially lucrative career opportunities.

The programme is delivered jointly between Heriot-Watt University and the University of Edinburgh. This means you will be enrolled as a student at both univerities and benefit from access to all the services and facilities each university has to offer.

Teaching is delivered by renowned academics from both Heriot-Watt and the University of Edinburgh - some classes will therefore take place at Heriot-Watt's campus and others at the University of Edinburgh campus. Successful students will graduate with a degree awarded jointly by Heriot-Watt and the University of Edinburgh and both names will appear on the graduation certificate.

Programme content

Core courses

Derivatives Markets
Derivative Pricing and Financial Modelling
Financial Markets
Discrete-Time Finance
Stochastic Analysis in finance
Credit Risk Modelling
Special Topics, including industry lead projects

Options

Statistical Methods
Financial Econometrics
Time Series Analysis
Modern Portfolio Theory
Optimisation Methods in Finance
Numerical Methods for PDEs
Simulation in Finance
Deterministic Optimisation Methods in Finance

Read less