• Swansea University Featured Masters Courses
  • University of Edinburgh Featured Masters Courses
  • University of York Featured Masters Courses
  • University of Glasgow Featured Masters Courses
  • Leeds Beckett University Featured Masters Courses
  • University of Leeds Featured Masters Courses
  • Regent’s University London Featured Masters Courses
  • Xi’an Jiaotong-Liverpool University Featured Masters Courses
De Montfort University Featured Masters Courses
University of Strathclyde Featured Masters Courses
Anglia Ruskin University Featured Masters Courses
Cass Business School Featured Masters Courses
University of Kent Featured Masters Courses
"stochastic" AND "models"…×
0 miles

Masters Degrees (Stochastic Models)

  • "stochastic" AND "models" ×
  • clear all
Showing 1 to 15 of 69
Order by 
The programme provides graduates with strong mathematical skills, the necessary computational techniques and finance background relevant to subsequent employment in a sector of finance such as investment banks, hedge funds, insurance companies and the finance departments of large corporations where mathematics plays a key role. Read more
The programme provides graduates with strong mathematical skills, the necessary computational techniques and finance background relevant to subsequent employment in a sector of finance such as investment banks, hedge funds, insurance companies and the finance departments of large corporations where mathematics plays a key role.

The depth of the mathematics taught should enable graduates to pursue research careers in stochastic analysis, financial mathematics or other relevant areas.

The period October to June is devoted to lectures, tutorials and practical sessions comprising the core and optional modules. This is followed by a period of about 14 weeks devoted to an individual project.

Core study areas include measure theory and martingales, stochastic models in finance, stochastic calculus and theory of stochastic pricing and a research project.

Optional study areas include programming and numerical methods, regular and chaotic dynamics, financial economics, functional analysis, elements of PDEs, static and dynamic optimisation, asset management and derivatives, and corporate finance

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/mathematical-finance/

Programme modules

Semester 1:
Compulsory Modules
- Introduction to Measure Theory and Martingales
- Stochastic Models in Finance

Optional Modules (choose two)
- Programming and Numerical Methods
- Regular and Chaotic Dynamics
- Financial Economics

Semester 2:
Compulsory Modules
- Stochastic Calculus and Theory of Stochastic Pricing
- Research Project

Optional Modules (choose three)
- Functional Analysis
- Elements of PDEs
- Static and Dynamic Optimisation
- Either Asset Management and Derivatives or Corporate Finance

Assessment

A combination of written examinations, reports, individual and group projects, and verbal presentations.

Careers and further study

This programme may lead to a wide range of employment within industry, the financial sectors, and research establishments. It may also provide an ideal background for postgraduate research in Stochastic Analysis, Probability Theory, Mathematical Finance and other relevant areas.

Scholarships and sponsorships

A number of part-fee studentships may be available to appropriately qualified international students.

Why choose mathematics at Loughborough?

Mathematics at Loughborough has a long history of innovation in teaching, and we have a firm research base with strengths in both pure and applied mathematics as well as mathematics education.

The Department comprises more than 34 academic staff, whose work is complemented and underpinned by senior visiting academics, research associates and a large support team.

The programmes on offer reflect our acknowledged strengths in pure and applied research in mathematics, and in some cases represent established collaborative training ventures with industrial partners.

- Mathematics Education Centre (MEC)
The Mathematics Education Centre (MEC) at Loughborough University is an internationally renowned centre of research, teaching, learning and support. It is a key player in many high-profile national initiatives.
With a growing number of academic staff and research students, the MEC provides a vibrant, supportive community with a wealth of experience upon which to draw.
We encourage inquiries from students who are interested in engaging in research into aspects of learning and teaching mathematics at Masters, PhD and Post Doc levels. Career prospects With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

- Career prospects
With 100% of our graduates in employment and/or further study six months after graduating, career prospects are excellent. Graduates
go on to work with companies such as BAE Systems, Citigroup, Experian, GE Aviation, Mercedes Benz, Nuclear Labs USA and PwC.

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/mathematics/mathematical-finance/

Read less
Take advantage of one of our 100 Master’s Scholarships to study Stochastic Processes. Theory and Application at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Stochastic Processes: Theory and Application at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

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
The MSc in Statistics aims to train professional statisticians for posts in industry, government, research and teaching. It also provides a suitable preparation for careers in other fields requiring a strong statistical background. Read more
The MSc in Statistics aims to train professional statisticians for posts in industry, government, research and teaching. It also provides a suitable preparation for careers in other fields requiring a strong statistical background.

*This course will be taught at the Canterbury campus*

Key benefits

- Statistics is thriving at Kent, and the research of the Group was rated in the top ten in the UK in the most recent Research Assessment Exercise. We are also one of the main hubs of the National Centre for Statistical Ecology.

- Accredited by the Royal Statistical Society (RSS)

Visit the website: https://www.kent.ac.uk/courses/postgraduate/166/statistics

Course Outline

The programme, which has recently been updated, trains professional statisticians for posts in industry, government, research and teaching. It provides a suitable preparation for careers in other fields requiring a strong statistical background. Core modules give a thorough grounding in modern statistical methods and there is the opportunity to choose additional topics to study.

Format and assessment

You undertake a substantial project in statistics, supervised by an experienced researcher. Some projects are focused on the analysis of particular complex data sets while others are more concerned with generic methodology.

You gain experience of analysing real data problems through practical classes and exercises. The programme includes training in the computer language R.

Modules:

- Stochastic Processes and Time Series (15 credits)
- Stochastic Models in Ecology and Medicine (15 credits)
- Analysis of Large Data Sets (15 credits)
- Practical Statistics and Computing (15 credits)
- Computational Statistics (15 credits)
- Project (60 credits)
- Probability and Classical Inference (15 credits)
- Advanced Regression Modelling (15 credits)
- Bayesian Statistics (15 credits)
- Principles of Data Collection (15 credits)

Assessment is through coursework and formal examinations.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

How to apply: https://www.kent.ac.uk/courses/postgraduate/apply/

Why study at The University of Kent?

- Shortlisted for University of the Year 2015
- Kent has been ranked fifth out of 120 UK universities in a mock Teaching Excellence Framework (TEF) exercise modelled by Times Higher Education (THE).
- In the Research Excellence Framework (REF) 2014, Kent was ranked 17th* for research output and research intensity, in the Times Higher Education, outperforming 11 of the 24 Russell Group universities
- Over 96% of our postgraduate students who graduated in 2014 found a job or further study opportunity within six months.
Find out more: https://www.kent.ac.uk/courses/postgraduate/why/

Postgraduate scholarships and funding

We have a scholarship fund of over £9 million to support our taught and research students with their tuition fees and living costs. Find out more: https://www.kent.ac.uk/scholarships/postgraduate/

English language learning

If you need to improve your English before and during your postgraduate studies, Kent offers a range of modules and programmes in English for Academic Purposes (EAP). Find out more here: https://www.kent.ac.uk/courses/postgraduate/international/english.html

Read less
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. Read more

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
This programme provides an exciting opportunity to gain an insight into the pressing economic issues of our times and learn how to assess, adapt and apply modern macroeconomic and microeconomic models to shape organisational or government policy. Read more
This programme provides an exciting opportunity to gain an insight into the pressing economic issues of our times and learn how to assess, adapt and apply modern macroeconomic and microeconomic models to shape organisational or government policy.

Our programme is designed to equip you with the skills of a professional economist, for careers in government, international organisations and business.

You will learn to understand and model issues affecting financial markets through the lens of an economist, assessing both the microeconomic impacts for firms, as well as the macroeconomic implications for the global economy.

You will develop advanced theoretical and quantitative skills, highly sought after by employers in the financial services sectors of industry and government, as well as transferable skills that will be of value for a range of other sectors.

There is the opportunity to specialise in various fields of finance. All students register for the MSc in Economics and Finance. However, depending on the choice and availability of modules and dissertation topic, it is possible to graduate with an MSc in Financial Economics instead.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/economics-finance/

Programme modules

Semester 1:
Compulsory Modules
- Macroeconomics Analysis
- Microeconomics Analysis
- Research Communication (two-semester module)
- Research Methods

Optional Modules (choose one)
- Financial Economics
- Introduction to Measure Theory and Martingales
- Stochastic Models in Finance
- The Financial System

Semester 2:
Compulsory Modules
- Further Quantitative Techniques for Finance and Economics
- Research Communication (two semester module)

Optional Modules (choose three)
- Applied Banking and Financial Modelling
- Asset Management and Derivatives
- Banking and Financial Markets
- Comparative Banking
- Corporate Finance
- Credit Risk Management
- Development Finance
- Economics and Energy Policy
- Stochastic Calculus and Theory of Stochastic Pricing

Choice of Semester 2 modules may be restricted by the option selected in Semester 1. The School reserves the right to vary the list of optional modules.

Summer:
- Dissertation

Assessment

75% examination and 25% coursework for most modules.

Careers and further study

Well-trained, numerate economists are in high demand in every sector. This programme prepares you for a career as a professional economist in banking, education, finance, government or industry, and for higher awards by research.

Example destinations include:
- HSBC – Analyst;
- SSR Group (Sweden) – Associate FX Broker;
- Siemens – Finance Officer.

Scholarships and sponsorships

School awards may be available for high-calibre national and international students.

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/economics-finance/

Read less
This programme is ideal for those who wish to pursue a career in the financial services sectors of industry or government, particularly banking and central banking. Read more
This programme is ideal for those who wish to pursue a career in the financial services sectors of industry or government, particularly banking and central banking.

Our modules are underpinned by the latest research and best practice, having been designed to equip you with up-to-date and relevant knowledge across a number of areas, including banking, finance and research methods.

The range of optional modules on the programme will enable you to specialise in areas of economics, banking and finance that best suit your career ambitions and interests.

Core study areas include financial economics, the financial system, research communication, research methods, asset management and derivatives, corporate finance, banking and financial markets, and further quantitative techniques.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/banking-finance/

Programme modules

Semester 1:
Compulsory modules
- Financial Economics
- Research Methods
- The Financial System
- Research Communication (two-semester module)

Optional modules (choose one):
- Introduction to Measure Theory and Martingales
- Macroeconomic Analysis
- Microeconomic Analysis
- Stochastic Models in Finance

Semester 2:
Core modules
- Asset Management and Derivatives and/or Corporate Finance
- Banking and Financial Markets
- Further Quantitative Techniques for Finance and Economics
- Research Communication (two-semester module)

Optional modules (choose one):
- Applied Banking and Financial Modelling
- Comparative Banking
- Development Finance
- Stochastic Calculus and Theory of Stochastic Pricing

Summer period:
Students satisfy the research requirement by examined participation in research seminars. Subject to special conditions, students may submit a dissertation instead.

Assessment

Modules are assessed by a combination of examinations and assignments.

Careers and further study

Example destinations include:
- Bank of China – Senior Manager
- China Everbright Bank – Client Manager
- Deutsche Bank – Analyst
- KPMG – Audit Associate
- National Australia Bank – Senior Assistant in Research
- RBS – Financial Transfer Officer

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/banking-finance/

Read less
This programme will help you develop professionally in the theory and practice of statistics and operational research (OR), providing the foundations for a successful career. Read more

Programme description

This programme will help you develop professionally in the theory and practice of statistics and operational research (OR), providing the foundations for a successful career.

This programme will prepare you for work in areas such as the medical and health industry, government, the financial sector and any other area where modern statistical tools and OR techniques are used. You will also develop the wider skills required for solving problems, working in teams and time management.

You will be able to identify appropriate statistical or operational techniques, which can be applied to practical problems, and will acquire extensive skills in modelling using the packages R for Statistics and Arena for simulation. In addition, you will acquire the ability to use high-level applications in Excel.

Programme structure

This MSc consists of lecture-based courses and practical, lab-based courses. You will be assessed by exams, written reports, programming assignments and a dissertation project.

Compulsory courses

Computing for Statistics
Fundamentals of Operational Research
Fundamentals of Optimization
Likelihood and Generalised Linear Models
Methodology, Modelling and Consulting Skills
Simulation
Statistical Regression Models
Statistical Theory
Stochastic Modelling

Option courses:

The Analysis of Survival Data
Categorical Data Analysis
Clinical Trials
Computing for Operational Research and Finance
Credit Scoring
Data Analysis
Genetic Epidemiology
Large Scale Optimization for Data Science
Machine Learning & Pattern Recognition
Multivariate Data Analysis
Nonparametric Regression
Operational Research in the Airline Industry
Operational Research in Telecommunications
Risk Analysis
Stochastic Models in Biology
Stochastic Optimization
Time Series Analysis and Forecasting

Career opportunities

This programme is ideal for students who wish to apply their statistics and operational research knowledge within a wide range of sectors including the medical and health sector, government and finance. The advanced problem-solving skills you will develop will be highly prized by many employers.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

Read less
The first intake for this course will be September 2015. The focus of this course is using mathematics to solve real world problems, such as in finance, energy, engineering or scientific research. Read more
The first intake for this course will be September 2015.

The focus of this course is using mathematics to solve real world problems, such as in finance, energy, engineering or scientific research. The combination of the applied nature of the mathematics that is taught, with the masters level of this course, makes this qualification highly attractive to employers.

Why study Applied Mathematics at Dundee?

Many of the topics taught are directly linked to the research that we do, so you will be learning at the cutting edge of applied mathematics.

We are a relatively small division and operate with an excellent staff/student ratio. One advantage of this is that we can get to know each student personally, and so can offer a friendly and supportive learning experience. Staff are ready and willing to help at all levels, and in addition, our Student-Staff Committee meets regularly to discuss matters of importance to our students.

We also offer students the chance to choose a selection of modules from other subject areas such as economics and finance.

Specialist software:
We have a wide selection of mathematical software packages such as MATLAB, Maple and COMSOL, which are used throughout the course.

Weekly seminar programme:
We have a weekly seminar programme in the mathematics division, which features talks in the areas of research strength in the division, Mathematical Biology, Applied Analysis, Magnetohydrodynamics and Numerical Analysis & Scientific Computing.

How you will be taught

You will learn by traditional methods such as lectures, tutorials, and workshops as well as via computer assisted learning. We teach the use of professional mathematical software packages in order to allow you to explore mathematics far beyond the limits of traditional teaching.

Individual reading and study takes a particularly important role in the Summer project. For the project, you will be guided to prepare your research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

What you will study

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 eight of the following:

Dynamical Systems
Computational Modelling
Statistics & Stochastic Models
Inverse Problems
Mathematical Oncology
Mathematical Ecology & Epidemiology
Mathematical Physiology
Fluid Dynamics
Optimization in Finance and Energy
Personal Transferable Skills
We also offer the option of relacing one or two mathematics modules with modules from subjects such as Global Risk Analysis, Energy Economics, Quantitative Methods and Econometrics for Finance.

How you will be assessed

Assessment is via a mix of open book continual assessment and closed book examinations, with a substantial project completed over the Summer.

Careers

Mathematics is central to the sciences, and to the development of a prosperous, modern society. The demand for people with mathematical qualifications is considerable, and a degree in mathematics is a highly marketable asset.

Mathematics graduates are consistently amongst those attracting the highest graduate salaries and can choose from an ever widening range of careers in research, industry, science, engineering, commerce, finance and education.

Read less
The Online MSc in Data Analytics covers 18 5-credit modules, two per semester over 9 semesters or 3 years, of which the Online Professional Diploma in Data Analytics covers the first 4. Read more
The Online MSc in Data Analytics covers 18 5-credit modules, two per semester over 9 semesters or 3 years, of which the Online Professional Diploma in Data Analytics covers the first 4. This first year is designed to introduce you to statistical and mathematical concepts in Data Analytics and Data Mining, and to get you started on programming with data. The second year is split between understanding the theory behind statistical and mathematical models for data via predictive analytics, and dealing with data sets at scale using Python and multivariate techniques. The final year covers some advanced methods: Monte Carlo, Bayesian Analysis, Time Series Data, and Complex Stochastic models. A provisional list of topics is as follows:

Read less
High-level training in statistics and the modelling of random processes for applications in science, business or health care. Read more
High-level training in statistics and the modelling of random processes for applications in science, business or health care.

For many complex systems in nature and society, stochastics can be used to efficiently describe the randomness present in all these systems, thereby giving the data greater explanatory and predictive power. Examples include statistical mechanics, financial markets, mobile phone networks, and operations research problems. The Master’s specialisation in Applied Stochastics will train you to become a mathematician that can help both scientists and businessmen make better decisions, conclusions and predictions. You’ll be able to bring clarity to the accumulating information overload they receive.

The members of the Applied Stochastics group have ample experience with the pure mathematical side of stochastics. This area provides powerful techniques in functional analysis, partial differential equations, geometry of metric spaces and number theory, for example. The group also often gives advice to both their academic colleagues, and organisations outside of academia. They will therefore not only be able to teach you the theoretical basis you need to solve real world stochastics problems, but also to help you develop the communications skills and professional expertise to cooperate with people from outside of mathematics.

See the website http://www.ru.nl/masters/mathematics/stochastics

Why study Applied Stochastics at Radboud University?

- This specialisation focuses both on theoretical and applied topics. It’s your choice whether you want to specialise in pure theoretical research or perform an internship in a company setting.
- Mathematicians at Radboud University are expanding their knowledge of random graphs and networks, which can be applied in the ever-growing fields of distribution systems, mobile phone networks and social networks.
- In a unique and interesting collaboration with Radboudumc, stochastics students can help researchers at the hospital with very challenging statistical questions.
- Because the Netherlands is known for its expertise in the field of stochastics, it offers a great atmosphere to study this field. And with the existence of the Mastermath programme, you can follow the best mathematics courses in the country, regardless of the university that offers them.
- Teaching takes place in a stimulating, collegial setting with small groups. This ensures that you’ll get plenty of one-on-one time with your thesis supervisor at Radboud University .
- More than 85% of our graduates find a job or a gain a PhD position within a few months of graduating.

Career prospects

Master's programme in Mathematics

Mathematicians are needed in all industries, including the banking, technology and service industries, to name a few. A Master’s in Mathematics will show prospective employers that you have perseverance, patience and an eye for detail as well as a high level of analytical and problem-solving skills.

Job positions

The skills learned during your Master’s will help you find jobs even in areas where your specialised mathematical knowledge may initially not seem very relevant. This makes your job opportunities very broad and is the reason why many graduates of a Master’s in Mathematics find work very quickly.
Possible careers for mathematicians include:
- Researcher (at research centres or within corporations)
- Teacher (at all levels from middle school to university)
- Risk model validator
- Consultant
- ICT developer / software developer
- Policy maker
- Analyst

PhD positions

Radboud University annually has a few PhD positions for graduates of a Master’s in Mathematics. A substantial part of our students attain PhD positions, not just at Radboud University, but at universities all over the world.

Our research in this field

The research of members of the Applied Stochastics Department, focuses on combinatorics, (quantum) probability and mathematical statistics. Below, a small sample of the research our members pursue.

Eric Cator’s research has two main themes, probability and statistics.
1. In probability, he works on interacting particles systems, random polymers and last passage percolation. He has also recently begun working on epidemic models on finite graphs.
2. In statistics, he works on problems arising in mathematical statistics, for example in deconvolution problems, the CAR assumption and more recently on the local minimax property of least squares estimators.

Cator also works on more applied problems, usually in collaboration with people from outside statistics, for example on case reserving for insurance companies or airplane maintenance. He has a history of changing subjects: “I like to work on any problem that takes my fancy, so this description might be outdated very quickly!”

Hans Maassen researches quantum probability or non-commutative probability, which concerns a generalisation of probability theory that is broad enough to contain quantum mechanics. He takes part in the Geometry and Quantum Theory (GQT) research cluster of connected universities in the Netherlands. In collaboration with Burkhard Kümmerer he is also developing the theory of quantum Markov chains, their asymptotic completeness and ergodic theory, with applications to quantum optics. Their focal point is shifting towards quantum information and control theory, an area which is rapidly becoming relevant to experimental physicists.

Ross Kang conducts research in probabilistic and extremal combinatorics, with emphasis on graphs (which abstractly represent networks). He works in random graph theory (the study of stochastic models of networks) and often uses the probabilistic method. This involves applying probabilistic tools to shed light on extremes of large-scale behaviour in graphs and other combinatorial structures. He has focused a lot on graph colouring, an old and popular subject made famous by the Four Colour Theorem (erstwhile Conjecture).

See the website http://www.ru.nl/masters/mathematics/stochastics

Read less
This programme is especially suitable for students wishing to gain an in-depth understanding of the field of employment relations as preparation for a career in Employment Relations, Labour Relations or related fields. Read more
This programme is especially suitable for students wishing to gain an in-depth understanding of the field of employment relations as preparation for a career in Employment Relations, Labour Relations or related fields.

In addition to providing students with a thorough grounding in the theory and practice of Employment Relations it is anticipated that on completion of the programme students will also meet the knowledge requirements for chartered membership of the Chartered Institute for Personnel and Development (CIPD), the professional body for HR, Employment Relations and related professions in the UK.

Taught by academics with a strong track record in both Employment Relations related research and practical experience of Employment Relations and HRM, the programme focuses on developing critical thinking and analytical skills alongside of the more practical skills required for a career in Employment Relations and HR.

Core subjects include employment law, developing skills for business leadership, HRM theory and practice, employee engagement, motivation and voice, work design, organisational change and development, wellbeing and work, employment relations, strategic HRM, HRM research methods, and a dissertation.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/employmentrelationsandhrm/

Programme modules

Semester 1:
Compulsory Modules
- Financial Economics
- Research Methods
- Research Communication (two-semester module)
- The Financial System

Optional Modules:
- Economics of Money and Finance
- Macroeconomic Analysis
- Microeconomics Analysis
- Stochastic Models in Finance
- Introduction to Measure Theory and Martingales

Semester 2:
Compulsory Modules
- Asset Management and Derivatives, or Corporate Finance
- Banking and Financial Markets
- Further Quantitative Techniques for Finance and Economics
- Research Communication (two-semester module)

Optional Modules (choose one)
- Applied Banking and Financial Modelling
- Comparative Banking
- Credit Risk Management
- Development Finance
- Stochastic Calculus and Theory of Stochastic Pricing

The School reserves the right to vary the list of optional modules.

Summer:
Students satisfy the research requirement by examined participation in research seminars. Subject to special conditions, students may submit a dissertation instead.

Careers and further study

Most large organisations in both the public and private sectors employ employment relations specialists. The grounding in Employment Relations and UK employment law, in addition to a grounding in more general HRM, that the programme provides also means graduates will be well equipped to bring expertise to both specialist Employment Relations and more general HR and management roles in both private and public sector organisations.

Scholarships and sponsorships

School awards may be available for high-calibre national and international students.

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/employmentrelationsandhrm/

Read less
Our department's Master’s program encompasses three fields. Statistical Theory, Actuarial Science and Financial Modelling. Students in the Statistical Theory field will study probability, inference, statistical computing and data analysis in depth. Read more
Our department's Master’s program encompasses three fields: Statistical Theory, Actuarial Science and Financial Modelling. Students in the Statistical Theory field will study probability, inference, statistical computing and data analysis in depth. Students in the Actuarial Science field will learn about survival analysis, risk, ruin, mortality and their connections with finance. Students in the Financial Modelling field will learn the theory and application of deterministic and stochastic models used in the banking industry.

Visit the website: http://grad.uwo.ca/prospective_students/programs/program_NEW.cfm?p=140

How to apply

For information on how to apply, please see: http://grad.uwo.ca/prospective_students/applying/index.html

Financing your studies

As one of Canada's leading research institutions, we place great importance on helping you finance your education. It is crucial that you devote your full energy to the successful completion of your studies, so we want to ensure that stable funding is available to you.
For information please see: http://grad.uwo.ca/current_students/student_finances/index.html

Read less
◾The University of Glasgow’s School of Mathematics and Statistics is ranked 3rd in Scotland and 11th in the UK (Complete University Guide 2017). Read more

Why this programme?

◾The University of Glasgow’s School of Mathematics and Statistics is ranked 3rd in Scotland and 11th in the UK (Complete University Guide 2017).
◾The Statistics Group at Glasgow is the largest statistics group in Scotland and internationally renowned for its research excellence.
◾Statistics obtained a 100% overall student satisfaction in the National Student Survey 2016. The subject continues to exceed student expectations by combining both teaching excellence and a supportive learning environment.

Programme Stucture

This flexible part-time programme is completed over three years. In the first two years you will be taking two courses each trimester. In the third year you will be working on a project and dissertation.

The courses are designed to allow you to work at your own pace, with milestones and assessment to be completed according to an agreed timetable.

The programme can be taken alongside full-time employment (around 10 hours of study per week are recommended).

Core courses
◾Stochastic Models and Probability
◾Learning from Data
◾Predictive Models
◾R Programming
◾Data Programming in Python
◾Data Management and Analytics using SAS
◾Advanced Predictive Models
◾Data Mining and Machine Learning I: Supervised and Unsupervised Learning
◾Data Mining and Machine Learning II: Big and Unstructured Data
◾Uncertainty Assessment and Bayesian Computation
◾High-performance Computing for Data Analytics
◾Data Analytics in Business and Industry

You will also carry out a 60 credit research project.

Online Distance Learning

Online distance learning at the University of Glasgow allows you to benefit from the outstanding educational experience that we are renowned for without having to relocate to our campus. You do not need to have experience of studying online as you will be guided through how to access and use all of our online resources.

Virtual Learning

Your courses will consist of rich interactive reading material, tutor-led videos and computer-led programming sessions. You will be provided with access to electronic articles and books for background reading. Regular online assessments will allow you to monitor your progress.

Collaborative learning

Community building and collaborative learning is a key focus of our online delivery and you will be encouraged and supported to interact with your fellow classmates and tutors in a variety of ways.

Requirements

All you need to participate in this online programme is a computer and internet access.

On-campus examinations

In the first year of the programme you will need to take three paper-based examinations, held on May 2018 (preliminary dates: May 7th to 9th, 2018). UK-based students will haver to take these examinations in Glasgow. Students from abroad can choose to either travel to Glasgow or take the examination in a local test centre, such as British Council offices. Test centres are subject to approval by the University and the candidate is responsible for any local fees charged by the test centre.

Read less
In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. Read more

Programme description

In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. The recent growth of data science has increased the awareness of the importance of statistics, with the analysis of data and interpretation of the results firmly embedded within this newly recognised field.

This programme is designed to train the next generation of statisticians with a focus on the newly recognised field of data science. The syllabus combines rigorous statistical theory with wider hands-on practical experience of applying statistical models to data. In particular the programme includes:

classical and Bayesian ideologies
linear and generalised linear models
computational statistics applied to a range of models and applications
regression
data analysis

Graduates will be in high demand. It is anticipated that the majority of students will be employed as statisticians within private and public institutions providing statistical advice/consultancy.

Programme structure

To be awarded the MSc degree you need to obtain a total of 180 credits. All students take courses during semester 1 and 2 to the value of 120 credits of which compulsory course units comprise 60 credits. Successful performance in these courses (assessed via coursework or examinations or both) permits you to start work on your dissertation (60 credits) for the award of the MSc degree. The dissertation will generally take the form of two consultancy-style case projects or an externally supervised project.

Compulsory courses (60 credits):

Statistical Theory (10 credits, semester 1)
Statistical Regression Models (10 credits, semester 1)
Bayesian Theory (10 credits, semester 1)
Statistical Programming (10 credits, semester 1)
Bayesian Data Analysis (10 credits, semester 2)
Likelihood and Generalised Linear Models (10 credits, semester 2)

Optional courses (60 credits) include:

Data Analysis (20 credits, semester 1)
Introductory Applied Machine Learning (10 credits, semester 1)
Text Technologies for Data Science (10 credits, semester 1)
Fundamentals of Optimization (10 credits, semester 1)
The Analysis of Survival Data (10 credits, semester 2)
Stochastic Modelling (10 credits, semester 2)
Multilevel Modelling (20 credits, semester 2)
Large Scale Optimization for Data Science (10 credits, semester 2)
Modern Optimization Methods for Big Data Problems (10 credits, semester 2)
Time Series Analysis and Forecasting (5 credits, semester 2)
Combinatorial Optimization (5 credits, semester 2)
Probabilistic Modelling and Reasoning (10 credits, semester 2)

Learning outcomes

At the end of this programme you will have:

knowledge and understanding of statistical theory and its applications within data science
the ability to formulate suitable statistical models for new problems, fit these models to real data and correctly interpret the results
the ability to assess the validity of statistical models and their associated limitations
practical experience of implementing a range of computational techniques using statistical software R and BUGS/JAGS

Career opportunities

Trained statisticians are in high demand both in public and private institutions. This programme will provide graduates with the necessary statistical skills, able to handle and analyse different forms of data, interpret the results and effectively communicate the conclusions obtained.

Graduates will have a deep knowledge of the underlying statistical principles coupled with practical experience of implementing the statistical techniques using standard software across a range of application areas, ensuring they are ideally placed for a range of different job opportunities.

The degree is also excellent preparation for further study in statistics or data science.

Read less
Programme structure. The programme offers four "core" modules, taken by all students, along with a variety of elective modules from which students can pick and choose. Read more
Programme structure
The programme offers four "core" modules, taken by all students, along with a variety of elective modules from which students can pick and choose. There are examinations and coursework in eight modules altogether, including the four core modules. Additionally, all students complete a dissertation.

Core modules
0.Probability and stochastics. This course provides the basics of the probabilistic ideas and mathematical language needed to fully appreciate the modern mathematical theory of finance and its applications. Topics include: measurable spaces, sigma-algebras, filtrations, probability spaces, martingales, continuous-time stochastic processes, Poisson processes, Brownian motion, stochastic integration, Ito calculus, log-normal processes, stochastic differential equations, the Ornstein-Uhlenbeck process.


0.Financial markets. This course is designed to cover basic ideas about financial markets, including market terminology and conventions. Topics include: theory of interest, present value, future value, fixed-income securities, term structure of interest rates, elements of probability theory, mean-variance portfolio theory, the Markowitz model, capital asset pricing model (CAPM), portfolio performance, risk and utility, portfolio choice theorem, risk-neutral pricing, derivatives pricing theory, Cox-Ross-Rubinstein formula for option pricing.


0.Option pricing theory. The key ideas leading to the valuation of options and other important derivatives will be introduced. Topics include: risk-free asset, risky assets, single-period binomial model, option pricing on binomial trees, dynamical equations for price processes in continuous time, Radon-Nikodym process, equivalent martingale measures, Girsanov's theorem, change of measure, martingale representation theorem, self-financing strategy, market completeness, hedge portfolios, replication strategy, option pricing, Black-Scholes formula.


0.Financial computing I. The idea of this course is to enable students to learn how the theory of pricing and hedging can be implemented numerically. Topics include: (i) The Unix/Linux environment, C/C++ programming: types, decisions, loops, functions, arrays, pointers, strings, files, dynamic memory, preprocessor; (ii) data structures: lists and trees; (iii) introduction to parallel (multi-core, shared memory) computing: open MP constructs; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.


0.Interest rate theory. An in-depth analysis of interest-rate modelling and derivative pricing will be presented. Topics include: interest rate markets, discount bonds, the short rate, forward rates, swap rates, yields, the Vasicek model, the Hull-White model, the Heath-Jarrow-Merton formalism, the market model, bond option pricing in the Vasicek model, the positive interest framework, option and swaption pricing in the Flesaker-Hughston model.

Elective modules

0.Portfolio theory. The general theory of financial portfolio based on utility theory will be introduced in this module. Topics include: utility functions, risk aversion, the St Petersburg paradox, convex dual functions, dynamic asset pricing, expectation, forecast and valuation, portfolio optimisation under budget constraints, wealth consumption, growth versus income.


0.Information in finance with application to credit risk management. An innovative and intuitive approach to asset pricing, based on the modelling of the flow of information in financial markets, will be introduced in this module. Topics include: information-based asset pricing – a new paradigm for financial risk management; modelling frameworks for cash flows and market information; applications to credit risk modelling, defaultable discount bond dynamics, the pricing and hedging of credit-risky derivatives such as credit default swaps (CDS), asset dependencies and correlation modelling, and the origin of stochastic volatility.

0.Mathematical theory of dynamic asset pricing. Financial modelling and risk management involve not only the valuation and hedging of various assets and their positions, but also the problem of asset allocation. The traditional approach of risk-neutral valuation treats the problem of valuation and hedging, but is limited when it comes to understanding asset returns and the behaviour of asset prices in the real-world 'physical' probability measure. The pricing kernel approach, however, treats these different aspects of financial modelling in a unified and coherent manner. This module introduces in detail the techniques of pricing kernel methodologies, and its applications to interest-rete modelling, foreign exchange market, and inflation-linked products. Another application concerns the modelling of financial markets where prices admit jumps. In this case, the relation between risk, risk aversion, and return is obscured in traditional approaches, but is made clear in the pricing kernel method. The module also covers the introduction to the theory of Lévy processes for jumps and its applications to dynamic asset pricing in the modern setting.

0.Financial computing II: High performance computing. In this parallel-computing module students will learn how to harness the power of a multi-core computer and Open MP to speed up a task by running it in parallel. Topics include: shared and distributed memory concepts; Message Passing and introduction to MPI constructs; communications models, applications and pitfalls; open MP within MPI; introduction to Graphics Processors; GPU computing and the CUDA programming model; CUDA within MPI; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.


0.Risk measures, preference and portfolio choice. The idea of this module is to enable students to learn a variety of statistical techniques that will be useful in various practical applications in investment banks and hedge funds. Topics include: probability and statistical models, models for return distributions, financial time series, stationary processes, estimation of AR processes, portfolio regression, least square estimation, value-at-risk, coherent risk measures, GARCH models, non-parametric regression and splines.

Research project

Towards the end of the Spring Term, students will choose a topic to work on, which will lead to the preparation of an MSc dissertation. This can be thought of as a mini research project. The project supervisor will usually be a member of the financial mathematics group. In some cases the project may be overseen by an external supervisor based at a financial institution or another academic institution.

Read less

Show 10 15 30 per page


Share this page:

Cookie Policy    X