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Masters Degrees (Computational Mathematics)

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The M.S. in Applied and Computational Mathematics program is designed to prepare students to join the workforce as a consulting mathematician or to pursue doctoral study in computational and industrial mathematics or other computationally-intensive field of study. Read more
The M.S. in Applied and Computational Mathematics program is designed to prepare students to join the workforce as a consulting mathematician or to pursue doctoral study in computational and industrial mathematics or other computationally-intensive field of study. 

Distinctive features include:

• Project-oriented approach in all courses - real-world industrial problems motivate coursework
• Team problem-solving practica emulate an industrial microcosm in which undergrads, grads, faculty, and industrial partners work together to study real-world problems
• Dual emphasis is placed on computational mathematics in the study of all real-world projects in each course of the curriculum

Students who complete the proposed program will:

• Acquire advanced knowledge of a wide variety of topics that span the realm of applied mathematics, including differential equations, discrete mathematics, probabilistic modelling, optimisation and statistical analysis. 
• Become adept at employing all steps of the mathematical modelling process in the analysis of real-world phenomena.
• Acquire expertise in using various forms of technology and in using, modifying, and creating numerical algorithms used in the analysis of real-world phenomena,
• Develop the valuable intuition of using the right tool for the right job.

Curriculum

Required modules:

MAT 500 Fundamentals of Applied Mathematics
MAT 548 Industrial Mathematics - Continuous Models
MAT 549 Industrial Mathematics - Discrete Models
MAT 552 Operations Research
MAT 553 Stochastic Modelling
MAT 554 Scientific Computing
MAT 555 Industrial Practicum - Continuous Models
STA 505 Mathematical Statistics I
MAT 556 Industrial Practicum - Discrete Models
STA 511 Intro Stat Computing & Data Management

Electives:

One three-credit elective must be chosen from one of the following

MAT 514 Theory Of Numbers
MAT 515 Algebra I
MAT 516 Algebra II
MAT 532 Geometry I
MAT 533 Geometry II
MAT 535 Topology
MAT 545 Real Analysis I
MAT 546 Real Analysis II
MAT 575 Complex Analysis I

An additional three credit elective must be chosen from any 500-level mathematics or statistics course not completed from the above list.

Collaborators and Local Industry

Representatives from the private sector consisting of mathematicians and scientists from large companies such as Vanguard, and PrimePay; employees of up-and-coming software companies such as iPipeline; and representatives of small privately-owned consulting firms and hedge fund companies, such as Wagner Associates and TFS Capital were consulted in the creation of this program.  We are continually expanding our network of collaborators within the private sector, with our newest collaborator being Stroud Preserve in West Chester.

Vastly different types of mathematical problems are studied by the members of this group.  Many have agreed to contribute to this M.S. program by way of delivering colloquium talks about their experiences in industry, and by creating and investigating real-world problems in our practicum courses.

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Financial Mathematics is a branch of Mathematics where advanced mathematical and statistical methods are developed for and applied to financial markets and financial management. Read more

Overview

Financial Mathematics is a branch of Mathematics where advanced mathematical and statistical methods are developed for and applied to financial markets and financial management. Its main aims are to quantify and hedge risks in the financial marketplace.

Effective computational methods are crucial for the successful use of mathematical modelling in finance. The MSc in Financial and Computational Mathematics is designed to reflect this combination of knowledge and skills so that its graduates are well equipped to enter the competitive job markets of quantitative finance and related fields.

The course is focused on computational techniques and mathematical modelling used in the financial industry and on the required background in finance. The course is provided by the School of Mathematical Sciences with valuable input from the School of Economics. To ensure that the degree keeps pace with changes in employer expectations and employment opportunities, the course has its own advisory board which consists of leading experts from the financial industry and academia.

Key facts:

- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 60 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).
- In the last independent Teaching Quality Assessment, the School scored 23 out of 24.
- The course has its own advisory board (see below) consisting of leading experts from the financial industry and academia.
- The course is offered in collaboration with the School of Economics.

Module details

Core modules include: financial mathematics, advanced financial mathematics, scientific computing and c++, advanced scientific computing, financial mathematics dissertation.

Optional Stream 1 (Maths/Stats and Computing): Optimisation, Time Series and Forecasting, Statistical Foundations.

Optional Stream 2A: Econometic Theory, Financial and Macro Econometrics, Time Series Econometrics, Mathematics for Engineering Management, Game Theory.

Optional Stream 2B: Microeconomic Analysis, Financial Economics, Options and Futures Markets, Mathematics for Engineering Management, Game Theory.

English language requirements for international students

IELTS: 6.5 (with no less than 6.0 in any element)

Further information



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Computational mathematics is relevant to almost every science, engineering, business and finance discipline, as well as many industrial sectors. Read more
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

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The ideas of applied mathematics pervade several applications in a variety of businesses and industries as well as government. Sophisticated mathematical tools are increasingly used to develop new models, modify existing ones, and analyze system performance. Read more

Program overview

The ideas of applied mathematics pervade several applications in a variety of businesses and industries as well as government. Sophisticated mathematical tools are increasingly used to develop new models, modify existing ones, and analyze system performance. This includes applications of mathematics to problems in management science, biology, portfolio planning, facilities planning, control of dynamic systems, and design of composite materials. The goal is to find computable solutions to real-world problems arising from these types of situations.

The master of science degree in applied and computational mathematics provides students with the capability to apply mathematical models and methods to study various problems that arise in industry and business, with an emphasis on developing computable solutions that can be implemented. The program offers options in discrete mathematics, dynamical systems, and scientific computing. Students complete a thesis, which includes the presentation of original ideas and solutions to a specific mathematical problem. The proposal for the thesis work and the results must be presented and defended before the advisory committee.

Curriculum

Several options available for course sequence:
-Discrete mathematics option
-Dynamical systems option
-Scientific computing option

See website for individual module details.

Other entry requirements

-Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
-Submit a personal statement of educational objectives.
-Have an undergraduate cumulative GPA of 3.0 or higher.
-Submit two letters of recommendation, and complete a graduate application.
-International applicants whose primary language is not English must submit scores from the Test of English as a Foreign Language (TOEFL). A minimum score of 550 (paper-based) or 79-80 (Internet-based) is required. International English Language Testing System (IELTS) scores are accepted in place of the TOEFL exam. Minimum scores vary; however, the absolute minimum score required for unconditional acceptance is 6.5. For additional information about the IELTS, please visit http://www.ielts.org. Those who cannot take the TOEFL will be required to take the Michigan Test of English Proficiency at RIT and obtain a score of 80 or higher.
-Although Graduate Record Examination (GRE) scores are not required, submitting them may enhance a candidate's acceptance into the program.
-A student may also be granted conditional admission and be required to complete bridge courses selected from among RIT’s existing undergraduate courses, as prescribed by the student’s adviser. Until these requirements are met, the candidate is considered a nonmatriculated student. The graduate program director evaluates the student’s qualifications to determine eligibility for conditional and provisional admission.

Additional information

Student’s advisory committee:
Upon admission to the program, the student chooses an adviser and forms an advisory committee. This committee oversees the academic aspects of the student’s program, including the selection of a concentration and appropriate courses to fulfill the program’s requirements.

Cooperative education:
Cooperative education enables students to alternate periods of study on campus with periods of full-time, paid professional employment. Students may pursue a co-op position after their first semester. Co-op is optional for this program.

Part-time study:
The program is ideal for practicing professionals who are interested in applying mathematical methods in their work and enhancing their career options. Most courses are scheduled in the late afternoon or early evening. The program may normally be completed in two years of part-time study.

Nonmatriculated students:
A student with a bachelor’s degree from an approved undergraduate institution, and with the background necessary for specific courses, may take graduate courses as a nonmatriculated student with the permission of the graduate program director and the course instructor. Courses taken for credit may be applied toward the master’s degree if the student is formally admitted to the program at a later date. However, the number of credit hours that may be transferred into the program from courses taken at RIT is limited for nonmatriculated students.

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Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem. Read more
Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem.

The programme closely follows the structure of our Applied Mathematical Sciences MSc and will equip you with the skill to perform efficient accurate computer simulations in a wide variety of applied mathematics, physics, chemical and industrial problems.

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;
Stochastic Simulation;
Applied Linear Algebra;
Numerical Analysis;

Optional Courses

Dynamical Systems;
Optimization;
Partial Differential Equations;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Functional Analysis;
Software Engineering Foundations;
Mathematical Biology and Medicine;
Biologically Inspired Computation;
Advanced Software Engineering;
Geometry;
Bayesian Inference;

Typical project subjects

Simulation of Granular Flow and Growing Sandpiles;
Finite Element Discretisation of ODEs and PDEs;
Domain Decomposition;
Computational Spectral Theory;
Mathematical Modelling of Crime;
Mathematical Modelling of Micro-electron Mechanical Systems.
Can we Trust Eigenvalues on a Computer?

The final part of the MSc is an extended project in computational mathematics, giving the opportunity to investigate a topic in some depth guided by leading research academics from our 5-rated mathematics and statistics groups.

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About the programme. In addition to being a science in its own right, mathematics plays a fundamental role in the quantitative areas of practically all other academic disciplines, particularly in the natural sciences, engineering, business administration, economics, medicine and psychology. Read more

About the programme

In addition to being a science in its own right, mathematics plays a fundamental role in the quantitative areas of practically all other academic disciplines, particularly in the natural sciences, engineering, business administration, economics, medicine and psychology. Mathematical results permeate nearly all facets of life and are a necessary prerequisite for the vast majority of modern technologies – and as our IT systems become increasingly powerful, we are able to mathematically handle enormous amounts of data and solve ever more complex problems.

Special emphasis is placed on developing students' ability to formalise given problems in a way that facilitates algorithmic processing as well as enabling them to choose or develop, and subsequently apply, suitable algorithms to solve problems in an appropriate manner. The degree programme is theoretical in its orientation, with strongly application-oriented components. Studying this programme, you can gain advanced knowledge in the mathematical areas of Cryptography, Computer Algebra, Algorithmic Algebra and Geometry, Image and Signals Processing, Statistics and Stochastic Simulation, Dynamical Systems and Control Theory as well as expert knowledge in Computer Science fields such as Data Management, Machine Learning and Data Mining.

Furthermore, you will have the chance to learn how to apply your knowledge to tackle problems in areas as diverse as Marketing, Predictive Analytics, Computational Finance, Digital Humanities, IT Security and Robotics.

Programme syllabus

The core modules consist of two mathematics seminars and the presentation of your master's thesis.The compulsory elective modules are divided into eight module groups:

1)   Algebra, Geometry and Cryptography

This module group imparts advanced results in the areas of algebra and geometry, which constitute the fundament for algorithmic calculations, particularly in cryptography but also in many other mathematical areas.

2)   Mathematical Logic and Discrete Mathematics

The theoretical possibilities and limitations of algorithm-based solutions are treated in this module group.

3)   Analysis, Numerics and Approximation Theory

Methods from the fields of mathematical analysis, applied harmonic analysis and approximation theory for modelling and approximating continuous and discrete data and systems as well as efficient numerical implementation and evaluation of these methods are the scope of this module group.

4) Dynamical Systems and Optimisation

Dynamical systems theory deals with the description of change over time. This module group is concerned with methods used for the modelling, analysis, optimisation and design of dynamical systems, as well as the numerical implementation of such techniques.

5) Stochastics, Statistics

This module group deals with methods for modelling and analysing complex random phenomena as well as the construction, analysis and optimisation of stochastic algorithms and techniques used in statistical data analysis.

6) Data Analysis and Data Management and Programming

This module group examines the core methods used in computer science for the analysis of data of heterogeneous modalities (e.g. multimedia data, social networks and sensor data) and for the realisation of data analysis systems.

7) Applications

In this module group, you will practise applying the mathematical methods learned in module groups 1 to 6 to real-world applications such as Marketing, Predictive Analytics and Computational Finance.

8) Key Competencies and Language Training

In this module group, you will choose seminars that develop your non-subject-specific skills, such as public speaking and academic writing and other soft skills; you may also undertake internships. This serves to complement your technical expertise gained during your degree studies and helps to prepare you for your professional life after university.



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The Master of Science in Mathematics (120 ECTS) is a research-based master’s programme in which you can specialize in the following fields of mathematics. Read more

The Master of Science in Mathematics (120 ECTS) is a research-based master’s programme in which you can specialize in the following fields of mathematics: Pure Mathematics: Algebra, Analysis and Geometry; and Applied Mathematics: Statistics, Financial Mathematics, Computational Mathematics, Plasma-Astrophysics. 

What is the Master of Mathematics all about?

Besides a solid, all-round education in mathematics, the programme offers you the possibility to focus on either pure or applied mathematics. This allows you to acquire both breadth of knowledge and depth in your own areas of interest. Pure and applied mathematics courses are firmly grounded in the core research activities of the Department of Mathematics. Gradually, you will gain experience and autonomy in learning how to cope with new concepts, higher levels of abstraction, new techniques, new applications, and new results. This culminates in the Master’s thesis, where you become actively involved in the research performed in the various mathematical research groups of the Departments of Mathematics, Physics, Astronomy and Computer Sciences.

 This is an initial Master's programme and can be followed on a full-time or part-time basis.

Structure

The programme of the Master of Science in Mathematics consists of 120 ECTS. You choose one of the two profiles – Pure Mathematics or Applied Mathematics (54 ECTS) – and one of the two options – Research Option or Professional Option (30 ECTS). The profile allows you to specialize either in pure mathematics (algebra, geometry, analysis), or in applied mathematics (statistics, computational mathematics, fluid dynamics).

There is one common course: ‘Mathematics of the 21st Century’ (6 ECTS). To complete the programme, you carry out a research project that results in a master’s thesis (30 ECTS).

Department

All staff members of the Department of Mathematics are actively involved in the two-year Master of Science in Mathematics programme. The academic staff at the Department of Mathematics consists of leading experts in their fields. Researchers in pure mathematics focus on algebraic geometry, group theory, differential geometry, functional analysis, and complex analysis. Researchers in mathematical statistics deal with extreme values, robust statistics, non-parametric statistics, and financial mathematics. Research in the applied mathematics group is in computational fluid dynamics and plasma-astrophysics.

Career perspectives

Mathematicians find employment in industry and in the banking, insurance, and IT sectors. Many graduates from the research option pursue a career in research and start a PhD in mathematics, mathematical physics, astrophysics, engineering, or related fields.



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Programme description. Computational Mathematics, in particular the physical applied areas and the theory and implementation of numerical methods and algorithms, have wide-ranging applications in both the public and private sectors. Read more

Programme description

Computational Mathematics, in particular the physical applied areas and the theory and implementation of numerical methods and algorithms, have wide-ranging applications in both the public and private sectors. More recently, in this era of ubiquitous and cheap computing power, there has been an explosion in the number of problems that require us to understand processes by modelling them, and to use data sets that are large. Thus the subject of Computational Mathematics has become increasingly prominent. Consequently there is high demand also for computational modellers and data scientists. This programme concentrates on the overlap and synergy between these fields.

Programme structure

The programme consists of 120 credits of courses in total during Semesters 1 and 2, followed by a 60 credit dissertation which is completed during the Summer. The courses taken will be dependent on the availability of courses each year which may be subject to change as curriculum develops to reflect a modern degree programme.

The first semester is composed of a combination of compulsory and optional courses. The compulsory courses will build strong applied mathematical and computational foundations. The curriculum is completed with optional courses in related subjects such as statistics and optimization.

The second semester is again composed of a combination of compulsory and optional courses, building on the skills gained in Semester 1. The compulsory courses include Research Skills, which will prepare you for the Summer Dissertation Project. The optional courses cover a wide range of areas including, for example, data science, high performance computing, and related disciplines such as Informatics and Physics.

The 60 credit individual dissertation will take the form of a supervised research-style project on a topic proposed by a staff member of the Applied and Computational Mathematics group. The aim of the project is to provide practical experience and skills for tackling scientific problems which require both computational approaches and mathematical insight. This will include identifying and applying appropriate mathematical and numerical techniques, interpreting the results, and presenting the conclusions.

Career opportunities

This programme will provide training in the tools and techniques of mathematical modelling and scientific computing, and will provide students with skills for problem solving using modern techniques of applied mathematics.



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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Erasmus Mundus Computational Mechanics at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Erasmus Mundus Computational Mechanics at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

Swansea University has gained a significant international profile as one of the key international centres for research and training in computational mechanics and engineering. As a student on the Master's course in Erasmus Mundus Computational Mechanics, you will be provided with in-depth, multidisciplinary training in the application of the finite element method and related state-of-the-art numerical and computational techniques to the solution and simulation of highly challenging problems in engineering analysis and design.

Key Features of Erasmus Mundus Computational Mechanics MSc

The Zienkiewicz Centre for Computational Engineering is acknowledged internationally as the leading UK centre for computational engineering research. It represents an interdisciplinary group of researchers who are active in computational or applied mechanics. It is unrivalled concentration of knowledge and expertise in this field. Many numerical techniques currently in use in commercial simulation software have originated from Swansea University.

The Erasmus Mundus MSc Computational Mechanics course is a two-year postgraduate programme run by an international consortium of four leading European Universities, namely Swansea University, Universitat Politècnica de Catalunya (Spain), École Centrale de Nantes (France) and University of Stuttgart (Germany) in cooperation with the International Centre for Numerical Methods in Engineering (CIMNE, Spain).

As a student on the Erasmus Mundus MSc Computational Mechanics course, you will gain a general knowledge of the theory of computational mechanics, including the strengths and weaknesses of the approach, appreciate the worth of undertaking a computational simulation in an industrial context, and be provided with training in the development of new software for the improved simulation of current engineering problems.

In the first year of the Erasmus Mundus MSc Computational Mechanics course, you will follow an agreed common set of core modules leading to common examinations in Swansea or Barcelona. In addition, an industrial placement will take place during this year, where you will have the opportunity to be exposed to the use of computational mechanics within an industrial context. For the second year of the Erasmus Mundus MSc Computational Mechanics, you will move to one of the other Universities, depending upon your preferred specialisation, to complete a series of taught modules and the research thesis. There will be a wide choice of specialisation areas (i.e. fluids, structures, aerospace, biomedical) by incorporating modules from the four Universities. This allows you to experience postgraduate education in more than one European institution.

Modules

Modules on the Erasmus Mundus MSc Computational Mechanics course can vary each year but you could expect to study the following core modules (together with elective modules):

Numerical Methods for Partial Differential Equations

Continuum Mechanics

Advanced Fluid Mechanics

Industrial Project

Finite Element Computational Analysis

Entrepreneurship for Engineers

Finite Element in Fluids

Computational Plasticity

Fluid-Structure Interaction

Nonlinear Continuum Mechanics

Computational Fluid Dynamics

Dynamics and Transient Analysis

Reservoir Modelling and Simulation

Accreditation

The Erasmus Mundus Computational Mechanics course is accredited by the Joint Board of Moderators (JBM).

The Joint Board of Moderators (JBM) is composed of the Institution of Civil Engineers (ICE), the Institution of Structural Engineers (IStructE), the Chartered Institution of Highways and Transportation (CIHT), and the Institute of Highway Engineers (IHE).

This degree is accredited as meeting the requirements for Further Learning for a Chartered Engineer (CEng) for candidates who have already acquired an Accredited CEng (Partial) BEng(Hons) or an Accredited IEng (Full) BEng/BSc (Hons) undergraduate first degree.

See http://www.jbm.org.uk for further information.

This degree has been accredited by the JBM under licence from the UK regulator, the Engineering Council.

Accreditation is a mark of assurance that the degree meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). An accredited degree will provide you with some or all of the underpinning knowledge, understanding and skills for eventual registration as an Incorporated (IEng) or Chartered Engineer (CEng). Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

Links with Industry

On the Erasmus Mundus MSc Computational Mechanics course, you will have the opportunity to apply your skills and knowledge in computational mechanics in an industrial context.

As a student on the Erasmus Mundus MSc Computational Mechanics course you will be placed in engineering industries, consultancies or research institutions that have an interest and expertise in computational mechanics. Typically, you will be trained by the relevant industry in the use of their in-house or commercial computational mechanics software.

You will also gain knowledge and expertise on the use of the particular range of commercial software used in the industry where you are placed.

Careers

The next decade will experience an explosive growth in the demand for accurate and reliable numerical simulation and optimisation of engineering systems.

Computational mechanics will become even more multidisciplinary than in the past and many technological tools will be, for instance, integrated to explore biological systems and submicron devices. This will have a major impact in our everyday lives.

Employment can be found in a broad range of engineering industries as this course provides the skills for the modelling, formulation, analysis and implementation of simulation tools for advanced engineering problems.

Student Quotes

“I gained immensely from the high quality coursework, extensive research support, confluence of cultures and unforgettable friendship.”

Prabhu Muthuganeisan, MSc Computational Mechanics



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Do you have an aptitude and passion for mathematics and statistics, a keen interest in finance and insurance and want to work for a major financial organisation in finance, insurance or the money market? This course will provide you with a deep understanding of the world of finance, and give you the ability to speak its 'language'. Read more
Do you have an aptitude and passion for mathematics and statistics, a keen interest in finance and insurance and want to work for a major financial organisation in finance, insurance or the money market? This course will provide you with a deep understanding of the world of finance, and give you the ability to speak its 'language'. This course combines theory with hands-on practical skills via an industry placement or research project – ensuring you graduate with the right skills increasingly being sought by banks and other financial institutions.

The Master of Financial Mathematics offers advanced training in the core areas of stochastic, financial and insurance modelling, statistical analysis and computational methodology, as well as in a wide range of elective topics from economics, econometrics, finance, mathematics and probability.

Graduates of this course are likely to enter specialist careers in research departments within banks, insurance and consultancy firms or derivatives of valuation and portfolio management within investment houses.

The School of Mathematical Sciences sits within the leading Faculty of Science at Monash University. This vibrant, dynamic and successful School is undergoing a period of growth with the appointment of several new senior academic staff including Professor Gregoire Loeper, Course Director for the Masters of Financial Mathematics. With mathematics as the fundamental underpinning of so many subject areas, sectors and disciplines, the School is also building ever stronger collaborations with relevant industries, including the financial sector.

Visit the website http://www.study.monash/courses/find-a-course/2016/financial-mathematics-s6001?domestic=true

Course Structure

The course is structured in three Parts. Part A. Orientation studies, Part B. Specialist studies, Part C. Applied professional practice. All students complete Part B. Depending upon prior qualifications, you may receive credit for Part A or Part C or a combination of the two.

Part A. Orientation studies
These studies provide an orientation to the field of Financial Mathematics. You will choose studies that complement your current knowledge relevant to financial mathematics, including principles of econometrics, mathematical methods and stochastic processes.

Part B. Specialist studies
These studies will provide you with advanced knowledge and skills relevant to thoughtful, innovative and evidence-based practice in financial modelling and analysis. You will acquire core knowledge of and skills in financial econometrics, and advanced mathematical modelling and computational methods in finance. You will complement these with study in areas of your choice, including interest rate modelling, Markov processes, statistical learning in finance, and global financial markets.

Part C. Applied professional practice
These studies will provide you with the opportunity to apply your knowledge skills developed in Part A and B to "real life" problems, through completing an industry project or an industry internship. Students admitted to the course who have a recognised honours degree or graduate diploma or graduate certificate in a cognate discipline including mathematics or statistics, will receive credit for this part however, should they wish to complete a 24 point research project as part of Part B they should consult with the course convenor.

For more information visit the faculty website - http://www.study.monash/media/links/faculty-websites/science

About Mathematical Sciences

The School of Mathematical Sciences at Monash University is leading the way towards finding effective solutions to some of society's most pressing problems. Maths is the language of science and forms the basis of most of modern science and engineering. Our enthusiastic mathematicians love finding the true magic and beauty in maths and subsequently pass this passion on to their students.

Teaching

Studying maths equips you with a range of valuable, unique skills. Some of the exciting areas mathematicians at Monash are working on include mathematical modelling to predict behaviour, analysis using pure maths, and stochastic processes involving risk, randomness and change.

Mathematics and statistics are also the two cornerstones for decision making and various quantitative activities in commerce, industry, education and defence. From direct and daily experience, most companies and organisations have realised that success depends critically on the level of analytical, quantitative and statistical skills of their workforce and they therefore seek employees with a sound mathematical training.

By studying mathematics at Monash, you will also develop general skills in problem-solving, critical thinking, modelling, learning, analysis, research and creativity, which can be used wherever your career may take you.

Research

The School of Mathematical Sciences focuses on these main areas of research:

- Applied and Computational Mathematics
- Pure Mathematics
- Stochastic Processes

Find out how to apply here - http://www.study.monash/courses/find-a-course/2016/financial-mathematics-s6001?domestic=true#making-the-application

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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). Read more

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

The MSc Mathematics course has been designed for students who wish to build on their BSc, extending their range of mathematics expertise across a broader spread of topics, and demonstrating their literature research skills through an extended dissertation.

Such a qualification will mark graduates out as having a broader and deeper understanding of mathematics, and the skills required to pursue a significant project with a high level of independence, presenting their results in a written report. This will give MSc Mathematics graduates an edge in the ever more competitive jobs market.

On the Mathematics course you will study different elements of mathematics in a broad sense - including mathematical elements of computing if desired - in addition to developing your research, project management, and written communication skills through a project you will undertake. As a student of MSc in Mathematics, you will be fully supported to ensure that your project further develops an excellent foundation for your future career plans.

Modules

Modules on the MSc Mathematics include:

• Algebraic coding theory

• Biomathematics

• Black-Scholes theory

• Data science

• Differential geometry

• Fourier analysis

• Ito calculus

• Lie theory

• Numerical analysis

• Partial differential equations

• Stochastic processes

• Statistical mechanics

• Topology

Please visit our website for a full description of modules for the MSc Mathematics.

On top of the Mathematics modules you study, you will also complete a dissertation as part of your studies.

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.

Mathematics students will benefit from the £31m Computational Foundry for computer and mathematical sciences which will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)

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, statistically analysis, marketing and sales.

Some of our Mathematics students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where Mathematics graduates will find plenty of career opportunities.

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.

http://www.swansea.ac.uk/postgraduate/taught/science/mscmathematics/

Student Profile

"Further to my studies at Swansea University as a Master of Science graduate in Financial Mathematics, I am currently working at Deutsche Bank in London as part of the Structured Financial Services team providing client services for corporate lending and debt portfolios. The complex nature of the Mathematics course has helped me become a logical decision maker and a highly skilled problem solver. These transferable skills are very useful in the world of Finance since the role is highly challenging working towards deadlines and structured transaction targets. My studies at Swansea University have also enriched me with leadership, motivational skills and have enhanced my communication skills. I work in a close team of 10 people within a large department which encourages a culture that strives towards learning and effective teamwork. I thoroughly enjoyed my time at Swansea University and cherish the many fond memories. I am so pleased to be expanding my horizon within a major financial centre."

Rhian Ivey, BSc Mathematics, MSc Mathematics and Computing for Finance



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Studying Mathematics at postgraduate level gives you a chance to begin your own research, develop your own creativity and be part of a long tradition of people investigating analytic, geometric and algebraic ideas. Read more
Studying Mathematics at postgraduate level gives you a chance to begin your own research, develop your own creativity and be part of a long tradition of people investigating analytic, geometric and algebraic ideas.

If your mathematical background is insufficient for direct entry to the MSc in Mathematics and its Applications, you may apply for this course. The first year of this Master's programme gives you a strong background in mathematics, equivalent to the Graduate Diploma in Mathematics, with second year studies following the MSc in Mathematics and its Applications.

Visit the website https://www.kent.ac.uk/courses/postgraduate/148/international-masters-in-mathematics-and-its-applications

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School.

The Mathematics Group at Kent ranked highly in the most recent Research Assessment Exercise. With 100% of the Applied Mathematics Group submitted, all research outputs were judged to be of international quality and 12.5% was rated 4*. For the Pure Mathematics Group, a large proportion of the outputs demonstrated international excellence.

The Mathematics Group also has an excellent track record of winning research grants from the Engineering and Physical Sciences Research Council (EPSRC), the Royal Society, the EU, the London Mathematical Society and the Leverhulme Trust.

Course structure

At least one modern application of mathematics is studied in-depth by each student. Mathematical computing and open-ended project work forms an integral part of the learning experience. You strengthen your grounding in the subject and gain a sound grasp of the wider relevance and application of mathematics.

There are opportunities for outreach and engagement with the public on mathematics.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

MA552 - Analysis (15 credits)
MA553 - Linear Algebra (15 credits)
MA588 - Mathematical Techniques and Differential Equations (15 credits)
MA591 - Nonlinear Systems and Mathematical Biology (15 credits)
MA593 - Topics in Modern Applied Mathematics (30 credits)
MA549 - Discrete Mathematics (15 credits)
MA572 - Complex Analysis (15 credits)
MA563 - Calculus of Variations (15 credits)
MA587 - Numerical Solution of Differential Equations (15 credits)
MA577 - Elements of Abstract Analysis (15 credits)
MA576 - Groups and Representations (15 credits)
MA574 - Polynomials in Several Variables (15 credits)
MA961 - Mathematical Inquiry and Communication (30 credits)
MA962 - Geometric Integration (15 credits)
MA964 - Applied Algebraic Topology (15 credits)
MA965 - Symmetries, Groups and Invariants (15 credits)
MA968 - Mathematics and Music (15 credits)
MA969 - Applied Differential Geometry (15 credits)
MA970 - Nonlinear Analysis and Optimisation (15 credits)
MA971 - Introduction to Functional Analysis (15 credits)
MA972 - Algebraic Curves in Nature (15 credits)
MA973 - Basic Differential Algebra (15 credits)
CB600 - Games and Networks (15 credits)
MA562 - Nonlinear Waves and Solitons (15 credits)
MA960 - Dissertation (60 credits)

Assessment

Closed book examinations, take-home problem assignments and computer lab assignments (depending on the module).

Programme aims

This programme aims to:

- provide a Master’s level mathematical education of excellent quality, informed by research and scholarship

- provide an opportunity to enhance your mathematical creativity, problem-solving skills and advanced computational skills

- provide an opportunity for you to enhance your oral communication, project design and basic research skills

- provide an opportunity for you to experience and engage with a creative, research-active professional mathematical environment

- produce graduates of value to the region and nation by offering you opportunities to learn about mathematics in the context of its application.

Study support

Postgraduate resources
The University’s Templeman Library houses a comprehensive collection of books and research periodicals. Online access to a wide variety of journals is available through services such as ScienceDirect and SpringerLink. The School has licences for major numerical and computer algebra software packages. Postgraduates are provided with computers in shared offices in the School. The School has two dedicated terminal rooms for taught postgraduate students to use for lectures and self-study.

Support
The School has a well-established system of support and training, with a high level of contact between staff and research students. There are two weekly seminar series: The Mathematics Colloquium at Kent attracts international speakers discussing recent advances in their subject; the Friday seminar series features in-house speakers and visitors talking about their latest work. These are supplemented by weekly discussion groups. The School is a member of the EPSRC-funded London Taught Course Centre for PhD students in the mathematical sciences, and students can participate in the courses and workshops offered by the Centre. The School offers conference grants to enable research students to present their work at national and international conferences.

Dynamic publishing culture
Staff publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Advances in Mathematics; Algebra and Representation Theory; Journal of Physics A; Journal of Symbolic Computations; Journal of Topology and Analysis. Details of recently published books can be found within the staff research interests section.

Global Skills Award
All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme (http://www.kent.ac.uk/graduateschool/skills/programmes/gsa.html). The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.

Careers

A postgraduate degree in Mathematics is a flexible and valuable qualification that gives you a competitive advantage in a wide range of mathematically oriented careers. Our programmes enable you to develop the skills and capabilities that employers are looking for including problem-solving, independent thought, report-writing, project management, leadership skills, teamworking and good communication.

Many of our graduates have gone on to work in international organisations, the financial sector, and business. Others have found postgraduate research places at Kent and other universities.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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The M.A. in Mathematics at West Chester University is a thirty-three credit master’s program, eighteen credits of core courses and fifteen credits of electives, which offers great flexibility. Read more
The M.A. in Mathematics at West Chester University is a thirty-three credit master’s program, eighteen credits of core courses and fifteen credits of electives, which offers great flexibility. Elective courses may be in mathematics education, statistics, computer science, pure mathematics, applied and computational mathematics, actuarial science, business, and others. By properly selecting their electives, our M.A. candidates may train for work in a large variety of fields, including, but not limited to, actuarial science, computer science, operations research, biomathematics, cryptography, teaching in a high school or a two-year college, research, economics, environmental mathematics, geophysical mathematics, air traffic control operations, photogrammetry, and many more. Upon completion of the M.A. in Mathematics, students are also well prepared to pursue a doctoral program in mathematics.

Curriculum

Required modules:

MAT 515 Algebra I
MAT 516 Algebra II
MAT 545 Real Analysis I
MAT 546 Real Analysis II
MAT 532 Geometry I
STA 505 Mathematical Statistics I

Electives:

A student may choose from among 500-level MAT course offerings, as well as MTE 507, MTE 508, MTE 512, and MTE 604. A student may select CSC or STA courses with approval of their advisor.

Capstone Experience:

A student may choose one of two different capstone experiences:

Thesis - Student selects MAT 609 and MAT 610, which replace 6 credits of electives.

Oral Comprehensive Exam in 3 different subject areas.

For more detailed information about the modules taught on this course, please visit the website:

http://catalog.wcupa.edu/graduate/sciences-mathematics/mathematics/#coursestext

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Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem. Read more
Accurate and efficient scientific computations lie at the heart of most cross-discipline collaborations. It is key that such computations are performed in a stable, efficient manner and that the numerics converge to the true solutions, dynamics of the physics, chemistry or biology in the problem.

The programme closely follows the structure of our Applied Mathematical Sciences MSc and will equip you with the skill to perform efficient accurate computer simulations in a wide variety of applied mathematics, physics, chemical and industrial problems.

The MSc, has at its core, fundamental courses in pure mathematics and students will be able to take options from both pure and applied mathematics.

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;
Functional Analysis;
Partial Differential Equations;
Pure Mathematics (recommended).

Optional Courses

Mathematical Ecology;
Optimization;
Numerical Analysis of ODEs;
Applied Mathematics;
Dynamical Systems;
Stochastic Simulation;
Applied Linear Algebra;
Partial Differential Equations;
Numerical Analysis;
Bayesian Inference and Computational Methods;
Geometry.

Typical project subjects

Domain Decomposition;
Mathematical Modelling of Crime;
The Geometry of Point Particles;
Can we Trust Eigenvalues on a Computer?;
Braess Paradox;
The Ising Model: Exact and Numerical Results;
Banach Alegbras.

The final part of the MSc is an extended project in computational mathematics, giving the opportunity to investigate a topic in some depth guided by leading research academics from our 5-rated mathematics and statistics groups.

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This programme is now closed but you may want to consider other courses such as the . Mathematics MSc. . . Read more

This programme is now closed but you may want to consider other courses such as the Mathematics MSc

The Financial Mathematics MSc programme enables graduates and professionals with a strong mathematical background to research, develop and apply quantitative and computational techniques to investment and risk management. Based in the Department of Mathematics, this course has a superb reputation for research-led teaching and strong links to industry.

  • A rigorous approach to quantitative finance taught entirely by the Department of Mathematics.
  • In-depth coverage of the skills needed for working in the financial, actuarial or related industry: probability theory, optimisation, statistics and computer implementation.
  • Unrivalled facilities in central London with City of London's financial centre close by, and with access to live market data in our Bloomberg Data Laboratory.
  • Flexible study programme offering the opportunity to study part-time.
  • King’s is a member of the London Graduate School in Mathematical Finance which provides advanced courses for students who wish to push beyond the MSc core syllabus.
  • Lecturers on the programme have extensive experience in consulting and work for financial companies and institutions such as Bank of Finland, Commerzbank, Deutsche Bank, Goldman Sachs, ION Trading, Standard Chartered Bank and Winton Capital Management.

Description

Financial Mathematics studies problems of optimal investment and risk management, and this course covers a diverse range of topics, from classical options pricing to post-crisis investment and risk management

Like any branch of applied mathematics, financial mathematics analyses a given problem by first building a mathematical model for it and then examining the model. Both steps require detailed knowledge in different areas of mathematics, including probability, statistics, optimisation, computer science and many more traditional fields of mathematics.

Our Financial Mathematics MSc course is a unique study pathway that encompasses the essential skills required for successful risk management, trading and research in quantitative finance: probability, statistics, optimisation, computing and financial markets. You will explore probability theories, risk neutral valuation, stochastic analysis as well as interest rate and credit risk modules. We also offer you the opportunity to study an additional zero-credit supportive module called mathematical analysis for financial mathematics.

The Financial Mathematics MSc programme offers you the choice to study either full or part-time and is made up of optional and required modules. You must take modules totalling 180 credits to complete the course. If you are studying full-time, you will complete the course in one year, from September to September. If you are studying part-time, your programme will take two years to complete, you will study the required modules in the first year, and a further selection of required and optional modules including the 60-credit financial mathematics report module in your second year.

Bloomberg terminal laboratory

King’s is one of only a few academic departments in the UK that offers full access to Bloomberg terminals. These terminals will provide you access to live financial data. They are heavily used within the financial industry, and the data they provide is critical in assisting traders in making investment decisions and for risk managers monitoring investment probabilities. We have 13 Bloomberg terminals available for exclusive use by the Financial Mathematics MSc programme.

You will use the Bloomberg terminals to:

  • Gain an intuition for the conduct of real financial markets
  • Develop potential investment strategies
  • Experience using real-world investment and risk management software and obtain data for research.

The skills you will learn from using the terminals are highly valued by employers. King’s is part of a strong network of financial mathematics in London with connections both in academia and in the industry.

We are also members of the University of London and by arrangement, you can enrol in optional modules at other institutions within the University of London, which includes Birkbeck, London School of Economics and Political Sciences, University College London and many others.

Course purpose

This programme is suitable for students or professionals with a strong mathematical background. It covers the principles and techniques of quantitative finance to prepare students for advanced work in the financial sector or research in mathematical finance.

Course format and assessment

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

Average per week: Three hours for 11 weeks per each 15 credit module.

You are expected to spend approximately 10 hours of effort for each credit (so for a typical module of 15 credits this means 150 hours of effort).

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations.  

Career destinations

Our graduates are highly sought after by investment banks, corporate risk management units, insurance companies, fund management institutions, financial regulatory bodies, brokerage firms, and trading companies. Recent employers of our graduates include, Capital Investment, Credit Suisse, European Bank for Reconstruction & Development, Fitch Ratings, HSBC and Morgan & Stanley. Some graduates have pursued research degrees in financial mathematics.

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