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Mathematics is at the heart of advances in science, engineering and technology, as well as being an indispensable problem-solving and decision-making tool in many other areas of life. Read more
Mathematics is at the heart of advances in science, engineering and technology, as well as being an indispensable problem-solving and decision-making tool in many other areas of life. This MSc course enables you to delve deeply into particular aspects of pure and applied mathematics, through a wide choice of modules in fascinating areas such as fractal geometry, coding theory and analytic theory. You’ll complete your MSc with a piece of independent study, exploring the history of modern geometry, advances in approximation theory, variational methods applied to eigenvalue problems, or algebraic graph theory and culminating in a dissertation on the topic of your choice.

Key features of the course

•Ideal for mathematically inclined scientists and engineers as well as mathematicians
•Extends your knowledge and refines your abilities to process information accurately, and critically analyse and communicate complex ideas
•Develops an enhanced skill set that will put you at an advantage in careers as diverse as mathematics, education, computer science, economics, engineering and finance.
•The most popular MSc in mathematics in the UK.
This qualification is eligible for a Postgraduate Loan available from Student Finance England. For more information, see Fees and funding

Course details

You can take a number of different routes towards your qualification - see the full module list for all options.

Modules

The modules in this qualification are categorised as entry, intermediate and dissertation. Check our website for start dates as some modules are not available for study every year.

Entry:

• Calculus of variations and advanced calculus (M820)
• Analytic number theory I (M823)

Intermediate:

• Nonlinear ordinary differential equations (M821)
• Applied complex variables (M828) - next available in October 2017 and following alternate years
• Analytic number theory II (M829) - next available in October 2018 and following alternate years
• Approximation theory (M832) - next available in October 2018 and following alternate years
• Advanced mathematical methods (M833) - next available in October 2017 and following alternate years
• Fractal geometry (M835) - next available in October 2017 and following alternate years
• Coding theory (M836) - next available in October 2018 and following alternate years
• Dissertation: Dissertation in mathematics (M840)

Module study order:

•You must normally pass at least one entry level module before studying an intermediate module.
•You must pass Analytic number theory I (M823) before studying Analytic number theory II (M829).
•You must normally pass four modules before studying the Dissertation in mathematics (M840).
•Some topics for the dissertation have prerequisite modules

Otherwise within each category modules may be studied in any order, and you may register for a module while studying a pre-requisite for that module (i.e. before you know whether you have passed the pre-requisite module or not).

To gain this qualification, you need 180 credits as follows:

150 credits from this list:

Optional modules

• Advanced mathematical methods (M833)
• Analytic number theory I (M823)
• Analytic number theory II (M829)
• Applied complex variables (M828)
• Approximation theory (M832)
• Calculus of variations and advanced calculus (M820)
• Coding theory (M836)
• Fractal geometry (M835)
• Nonlinear ordinary differential equations (M821)

Plus

Compulsory module

Dissertation in mathematics (M840)

The modules quoted in this description are currently available for study. However, as we review the curriculum on a regular basis, the exact selection may change over time.

Credit transfer

For this qualification, we do not allow you to count credit for study you have already done elsewhere.

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Candidates who have a good undergraduate (BSc) degree or equivalent but whose mathematical background is insufficient for direct entry to the MSc programme may apply for a place on the conversion year for the MSc in Mathematical Finance. Read more
Candidates who have a good undergraduate (BSc) degree or equivalent but whose mathematical background is insufficient for direct entry to the MSc programme may apply for a place on the conversion year for the MSc in Mathematical Finance.

A place on the conversion year is normally offered together with a conditional offer for the MSc in Mathematical Finance in the following year, subject to successfully completing the conversion year. The normal progression requirement for progression from the conversion year to the MSc in Mathematical Finance is a final weighted average at 2:1 level (60% or above) for the modules taken in the conversion year.

Programme structure

The conversion year consists of a selection of modules to the value of 120 credits being part of the undergraduate degree in Mathematics and Finance at the University of York, with emphasis on the mathematical aspects of the course. Module choice is subject to prerequisites, timetabling constraints, availability of modules, and is subject to approval by the programme director.

The available modules may vary from year to year but are likely to include:

Term 1 (Autumn)
-Calculus (30 credits) (continues into Spring and Summer Terms)
-Algebra (20 credits) (continues into Spring and Summer Terms)
-Introduction to Probability and Statistics (20 credits)
-Statistics I (10 credits)
-Applied Probability (10 credits)
-Differential Equations (10 credits)
-Mathematical Finance I MAT00015H (10 credits)

Terms 2 and 3 (Spring and Summer Terms)
-Calculus (30 credits) (starts in Autumn, continues through Spring and completes in Summer Term)
-Algebra (20 credits) (starts in Autumn, continues through Spring and completes in Summer Term)
-Introduction to Applied Mathematics (20 credits) (starts in Spring Term, continues into Summer Term)
-Real Analysis (20 credits) (starts in Spring Term, continues into Summer Term)
-Linear Algebra (20 credits) (starts in Spring Term, continues into Summer Term)
-Vector Calculus (20 credits) (starts in Spring Term, continues into Summer Term)
-Statistics II (20 credits) (starts in Spring Term, continues into Summer Term)
-Numerical Analysis (10 credits) (Spring Term only)
-Mathematical Finance II (10 credits) (Spring Term only)

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See the department website - http://www.cis.rit.edu/graduate-programs/master-science. The master of science program in imaging science prepares students for positions in research in the imaging industry or in the application of various imaging modalities to problems in engineering and science. Read more
See the department website - http://www.cis.rit.edu/graduate-programs/master-science

The master of science program in imaging science prepares students for positions in research in the imaging industry or in the application of various imaging modalities to problems in engineering and science. Formal course work includes consideration of the physical properties of radiation-sensitive materials and processes, the applications of physical and geometrical optics to electro-optical systems, the mathematical evaluation of image forming systems, digital image processing, and the statistical characterization of noise and system performance. Technical electives may be selected from courses offered in imaging science, color science, engineering, computer science, science, and mathematics. Both thesis and project options are available. In general, full-time students are required to pursue the thesis option, with the project option targeted to part-time and online students who can demonstrate that they have sufficient practical experience through their professional activities.

Faculty within the Center for Imaging Science supervise thesis research in areas of the physical properties of radiation-sensitive materials and processes, digital image processing, remote sensing, nanoimaging, electro-optical instrumentation, vision, medical imaging, color imaging systems, and astronomical imaging. Interdisciplinary efforts are possible with other colleges across the university.

The program can be completed on a full- or a part-time basis. Some courses are available online, specifically in the areas of color science, remote sensing, medical imaging, and digital image processing.

Plan of study

All students must earn 30 credit hours as a graduate student. The curriculum is a combination of required core courses in imaging science, elective courses appropriate for the candidate’s background and interests, and either a research thesis or graduate paper/project. Students must enroll in either the research thesis or graduate paper/project option at the beginning of their studies.

Core courses

Students are required to complete the following core courses: Fourier Methods for Imaging (IMGS-616), Image Processing and Computer Vision (IMGS-682), Optics for Imaging (IMGS-633), and either Radiometry (IMGS-619) or The Human Visual System (IMGS-620).

Speciality track courses

Students choose two courses from a variety of tracks such as: digital image processing, medical imaging, electro-optical imaging systems, remote sensing, color imaging, optics, hard copy materials and processes, and nanoimaging. Tracks may be created for students interested in pursuing additional fields of study.

Research thesis option

The research thesis is based on experimental evidence obtained by the student in an appropriate field, as arranged between the student and their adviser. The minimum number of thesis credits required is four and may be fulfilled by experiments in the university’s laboratories. In some cases, the requirement may be fulfilled by work done in other laboratories or the student's place of employment, under the following conditions:

1. The results must be fully publishable.

2. The student’s adviser must be approved by the graduate program coordinator.

3. The thesis must be based on independent, original work, as it would be if the work were done in the university’s laboratories.

A student’s thesis committee is composed of a minimum of three people: the student’s adviser and two additional members who hold at least a master's dgeree in a field relevant to the student’s research. Two committee members must be from the graduate faculty of the center.

Graduate paper/project option

Students with demonstrated practical or research experience, approved by the graduate program coordinator, may choose the graduate project option (3 credit hours). This option takes the form of a systems project course. The graduate paper is normally performed during the final semester of study. Both part- and full-time students may choose this option, with the approval of the graduate program coordinator.

Admission requirements

To be considered for admission to the MS in imaging science, candidates must fulfill the following requirements:

- Hold a baccalaureate degree from an accredited institution (undergraduate studies should include the following: mathematics, through calculus and including differential equations; and a full year of calculus-based physics, including modern physics. It is assumed that students can write a common computer program),

- Submit a one- to two-page statement of educational objectives,

- Submit official transcripts (in English) of all previously completed undergraduate or graduate course work,

- Submit letters of recommendation from individuals familiar with the applicant’s academic or research capabilities,

- Submit scores from the Graduate Record Exam (GRE) (requirement may be waived for those not seeking funding from the Center for Imaging Science), and

- Complete a graduate application.

- International applicants whose native language is not English must submit scores from the Test of English as a Foreign Language. Minimum scores of 600 (paper-based) or 100 (Internet-based) are required. Students may also submit scores from the International English Language Testing System. The minimum IELTS score is 7.0. International students who are interested in applying for a teaching or research assistantship are advised to obtain as high a TOEFL or IELTS score as possible. These applicants also are encouraged to take the Test of Spoken English in order to be considered for financial assistance.

Applicants seeking financial assistance from the center must have all application documents submitted to the Office of Graduate Enrollment Services by January 15 for the next academic year.

Additional information

- Bridge courses

Applicants who lack adequate preparation may be required to complete bridge courses in mathematics or physics before matriculating with graduate status.

- Maximum time limit

University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.

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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.

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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/

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To gain this qualification, you need 180 credits as follows. Stage 1. 60 credits from List A. List A. optional modules. Advanced routing - CCNP 1 (T824). Read more

Modules

To gain this qualification, you need 180 credits as follows:

Stage 1

60 credits from List A:

List A: optional modules

• Advanced routing - CCNP 1 (T824)
• Capacities for managing development (T878)
• Conflict and development (T879)
• Development: context and practice (T877)
• Environmental monitoring and protection (T868)
• Finite element analysis: basic principles and applications (T804)
• Institutional development (TU872)
• Making environmental decisions (T891)
• Managing for sustainability (T867)
• Managing systemic change: inquiry, action and interaction (TU812)
• Managing technological innovation (T848)
• Manufacture materials design (T805)
• Multilayer switching - CCNP 3 (T826)
• Network security (T828)
• Optimising networks - CCNP 4 (T827)
• Problem solving and improvement: quality and other approaches (T889)
• Strategic capabilities for technological innovation (T849)
• Thinking strategically: systems tools for managing change (TU811)

Plus 30 credits from List B:

List B: optional modules

• Advanced mathematical methods (M833)
• Advanced routing - CCNP 1 (T824)
• Analytic number theory I (M823)
• Analytic number theory II (M829)
• Applied complex variables (M828)
• Approximation theory (M832)
• Calculus of variations and advanced calculus (M820)
• Capacities for managing development (T878)
• Coding theory (M836)
• Conflict and development (T879)
• Data management (M816)
• Developing research skills in science (S825)
• Development: context and practice (T877)
• Digital forensics (M812)
• Environmental monitoring and protection (T868)
• Finite element analysis: basic principles and applications (T804)
• Fractal geometry (M835)
• Information security (M811)
• Institutional development (TU872)
• Making environmental decisions (T891)
• Managing for sustainability (T867)
• Managing systemic change: inquiry, action and interaction (TU812)
• Managing technological innovation (T848)
• Manufacture materials design (T805)
• Multilayer switching - CCNP 3 (T826)
• Network security (T828)
• Nonlinear ordinary differential equations (M821)
• Optimising networks - CCNP 4 (T827)
• Problem solving and improvement: quality and other approaches (T889)
• Project management (M815)
• Researching mathematics learning (ME825)*
• Software development (M813)
• Software engineering (M814)
• Space science (S818) NEW1
• Strategic capabilities for technological innovation (T849)
• Thinking strategically: systems tools for managing change (TU811)

* 60-credit module of which only 30 credits count towards this qualification

Plus 30 credits from:

Compulsory module

Team engineering (T885)

Stage 2

60 credits from:

Compulsory module

Research project (T802)

The modules quoted in this description are currently available for study. However, as we review the curriculum on a regular basis, the exact selection may change over time.

Credit transfer

Credit transfer is not permitted for the MSc except for any awarded as part of the Postgraduate Diploma in Engineering.
For further advice and guidance, please email us.

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Working at a frontier of mathematics that intersects with cutting edge research in physics. Mathematicians can benefit from discoveries in physics and conversely mathematics is essential to further excel in the field of physics. Read more
Working at a frontier of mathematics that intersects with cutting edge research in physics.

Mathematicians can benefit from discoveries in physics and conversely mathematics is essential to further excel in the field of physics. History shows us as much. Mathematical physics began with Christiaan Huygens, who is honoured at Radboud University by naming the main building of the Faculty of Science after him. By combining Euclidean geometry and preliminary versions of calculus, he brought major advances to these areas of mathematics as well as to mechanics and optics. The second and greatest mathematical physicist in history, Isaac Newton, invented both the calculus and what we now call Newtonian mechanics and, from his law of gravity, was the first to understand planetary motion on a mathematical basis.

Of course, in the Master’s specialisation in Mathematical Physics we look at modern mathematical physics. The specialisation combines expertise in areas like functional analysis, geometry, and representation theory with research in, for example, quantum physics and integrable systems. You’ll learn how the field is far more than creating mathematics in the service of physicists. It’s also about being inspired by physical phenomena and delving into pure mathematics.

At Radboud University, we have such faith in a multidisciplinary approach between these fields that we created a joint research institute: Institute for Mathematics, Astrophysics and Particle Physics (IMAPP). This unique collaboration has lead to exciting new insights into, for example, quantum gravity and noncommutative geometry. Students thinking of enrolling in this specialisation should be excellent mathematicians as well as have a true passion for physics.

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

Why study Mathematical Physics at Radboud University?

- This specialisation is one of the few Master’s in the world that lies in the heart of where mathematics and physics intersect and that examines their cross-fertilization.
- You’ll benefit from the closely related Mathematics Master’s specialisations at Radboud University in Algebra and Topology (and, if you like, also from the one in Applied Stochastics).
- Teaching takes place in a stimulating, collegial setting with small groups. This ensures that at Radboud University you’ll get plenty of one-on-one time with your thesis supervisor.
- You partake in the Mastermath programme, meaning you can follow the best mathematics courses, regardless of the university in the Netherlands that offers them. It also allows you to interact with fellow mathematic students all over the country.
- As a Master’s student you’ll get the opportunity to work closely with the mathematicians and physicists of the entire IMAPP research institute.
- More than 85% of our graduates find a job or a gain a PhD position within a few months of graduating. About half of our PhD’s continue their academic careers.

Career prospects

Mathematicians are needed in all industries, including the industrial, banking, technology and service industry and also within management, consultancy and education. 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 indeed and is 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 Mathematical Physics Department, emphasise operator algebras and noncommutative geometry, Lie theory and representation theory, integrable systems, and quantum field theory. Below, a small sample of the research our members pursue.

Gert Heckman's research concerns algebraic geometry, group theory and symplectic geometry. His work in algebraic geometry and group theory concerns the study of particular ball quotients for complex hyperbolic reflection groups. Basic questions are an interpretation of these ball quotients as images of period maps on certain algebraic geometric moduli spaces. Partial steps have been taken towards a conjecture of Daniel Allcock, linking these ball quotients to certain finite almost simple groups, some even sporadic like the bimonster group.

Erik Koelink's research is focused on the theory of quantum groups, especially at the level of operator algebras, its representation theory and its connections with special functions and integrable systems. Many aspects of the representation theory of quantum groups are motivated by related questions and problems of a group representation theoretical nature.

Klaas Landsman's previous research programme in noncommutative geometry, groupoids, quantisation theory, and the foundations of quantum mechanics (supported from 2002-2008 by a Pioneer grant from NWO), led to two major new research lines:
1. The use of topos theory in clarifying the logical structure of quantum theory, with potential applications to quantum computation as well as to foundational questions.
2. Emergence with applications to the Higgs mechanism and to Schroedinger's Cat (aka as the measurement problem). A first paper in this direction with third year Honours student Robin Reuvers (2013) generated worldwide attention and led to a new collaboration with experimental physicists Andrew Briggs and Andrew Steane at Oxford and philosopher Hans Halvorson at Princeton.

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

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The four-semester program is designed for students who wish to combine their liberal arts, fine arts, science, or engineering background with business to create a dynamic career track. Read more
The four-semester program is designed for students who wish to combine their liberal arts, fine arts, science, or engineering background with business to create a dynamic career track. While no previous business coursework is required, a working knowledge of calculus and well-developed English and computer skills are very beneficial.

The program provides a generalist perspective, and the flexibility of the curriculum allows you to concentrate in one of five career specializations: Finance, Leadership Studies, Supply Chain Management, Management Information Systems, and Marketing.

Graduate Degree Offered

MBA with concentrations in:
- Finance
- Leadership Studies
- Supply Chain Management
- Management Information Systems
- Marketing
Concentrations are optional.
In addition to a concentration, students who take selected quantitative coursework will also have the opportunity to earn a focus in business analytics.

Consider the Benefits

- Builds solid foundation in business fundamentals
- Features integrated courses that foster a multidisciplinary perspective
- Combines a generalist perspective with opportunities to specialize

Program Objective

The Four-Semester Program is designed for students who wish to combine their liberal arts, fine arts, science, or engineering background with business to create a dynamic career track. While no previous business coursework is required, a working knowledge of calculus and well-developed English and computer skills are very beneficial.

Developing Core Essentials

During the first year, expect to develop the fundamentals of business through the core courses that provide the base for more individualized study in the second year. These courses include the functional areas of business that equip you with the important analytical tools essential for critical decision-making. Students work in task-oriented teams, drawing upon the experience and skills of peers to solve challenging business problems. Effective leadership requires students to see the big picture and to understand how all the functional areas are linked. Additionally, the first year emphasizes the role of managers in today's society by integrating social responsibility, leadership, and cultural sensitivity. Communication skills, critical to business success, are also fine-tuned through the written and oral communications course. Furthermore, the first year focuses on career preparation through the professional development course that includes job search strategies, leadership assessment, development of networking and interviewing skills, and interaction with employer guest speakers.

Flexible Curriculum

Internships help launch your career.
In the second year of the program, students have the opportunity to explore various career tracks through numerous elective course offerings, including cross-disciplinary electives, real-world project courses and corporate internships.
Because experiential learning plays an integral part in fulfilling career goals, the school requires every full-time MBA student to obtain an internship during the course of the program. (Internships may be used towards fulfilling an elective course requirement).

All applicants must submit the following:

- Online graduate degree application and application fee
- Transcripts from each college/university which you have attended
- Two letters of recommendation
- Personal statement (2-3 pages) describing your reasons for pursuing graduate study, your career aspirations, your special interests within your field, and any unusual features of your background that might need explanation or be of interest to your program's admissions committee.
- Resume or Curriculum Vitae (max. 2 pages)
- Official GMAT scores

And, for international applicants:
- International Student Financial Statement form
- Official bank statement/proof of support
- Official TOEFL, IELTS, or PTE Academic scores
----MBA applicant minimum TOEFL scores:
*96 on the Internet-based exam
*590 on the paper exam
----MBA applicant minimum IELTS score:
*7.0
----MBA applicant minimum PTE Academic score:
*65

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Subject Knowledge Enhancement Courses (SKEs) are about improving subject knowledge in preparation for a Teacher Training course. You will be taught by experienced teachers of mathematics, and will spend 2 of the 12 weeks in a school where you will have the opportunity to apply your subject knowledge. Read more
Subject Knowledge Enhancement Courses (SKEs) are about improving subject knowledge in preparation for a Teacher Training course. You will be taught by experienced teachers of mathematics, and will spend 2 of the 12 weeks in a school where you will have the opportunity to apply your subject knowledge. You will benefit from extensive use of interactive methods which will help you learn mathematics and form links with colleagues which will be invaluabe throughout the PGCE programme. This course is available to PGCE offer holders at London Metropolitan University or at other universities whose offer stipulates completion of subject knowledge enhancement.

More about this course

The course will cover higher level GCSE level and early A level Pure Mathematics and Statistics. There will be mathematical modules on: Algebra of Polynomial Functions and Equations, Trigonometry and Continuous Functions, Calculus, Data Handling and Statistics, Euclidean Geometry. An introduction to educational issues will include reading, films, and an introduction to current issues in education policy.

We will use mathematics materials which are commonly used in classrooms to promote interactive engagement in mathematics including group work and extensive use of ICT. The course will include an introduction to relevant themes in teaching and learning which will also develop reading and writing skills necessary for the PGCE. There will be a two week school placement where you will have an opportunity to observe and participate in classroom mathematics.

The course will be assessed by a continuous assessment portfolio and a final examination. The portfolio will include mathematical tasks, written assignments, a profile of the school placement and work designed to practice specific areas of the curriculum. The final examination will include a GCSE Higher Mathematics paper (calculator and non-calculator papers) and a paper of relevant questions of A-level standard.

Professional accreditation

The course is funded by the National College for Teaching and Leadership (NCTL), and London Met is approved to provide SKE with NCTL funding for either maths or French.

Modular structure

The twelve-week course will be based at the University for four days each week Tuesday to Friday, with the exception of a two week placement in schools which will be arranged for you. You will be following a course which focusses on the content of higher GCSE level and early A level Pure Mathematics and Statistics.

There will be mathematical modules on: Algebra of Polynomial Functions and Equations, Trigonometry and Continuous Functions, Calculus, Data Handling and Euclidean Statistics, and Geometry. An introduction to educational issues will include reading, films, and an introduction to current issues in education policy. There will be a 2 week placement in a mathematics department in a secondary school.

You will learn mathematics in a variety of ways including mathematics software, group work and by following targets tailored to your own needs. Learning mathematics in these ways will give you first-hand experience of the pedagogies which you will use in the PGCE course. The school placement will give you the chance to see mathematics teaching in a school and you will, by completing specially designed evaluation tasks, develop reading and writing skills necessary for the PGCE. Throughout the course there will be regular tutorials to monitor your progress and provide help and guidance to make the London Met maths enhancement course a successful first step in your teaching career.

[[After the course[[
You will be able to move onto the PGCE programme upon successful completion of the SKE course.

Funding

Our Subject Knowledge Enhancement courses (SKEs) are 12 weeks long. Your fees are paid by the National College of Teaching and Leadership (NCTL). In addition, you will receive a bursary of £2,400 or £800 per month. More information on Enhancement Courses is available from the DfE.

Moving to one campus

Between 2016 and 2020 we're investing £125 million in the London Metropolitan University campus, moving all of our activity to our current Holloway campus in Islington, north London. This will mean the teaching location of some courses will change over time.

Whether you will be affected will depend on the duration of your course, when you start and your mode of study. The earliest moves affecting new students will be in September 2017. This may mean you begin your course at one location, but over the duration of the course you are relocated to one of our other campuses. Our intention is that no full-time student will change campus more than once during a course of typical duration.

All students will benefit from our move to one campus, which will allow us to develop state-of-the-art facilities, flexible teaching areas and stunning social spaces.

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This course is for people who need to strengthen their maths knowledge fairly quickly before starting their training to become a secondary mathematics teacher. Read more
This course is for people who need to strengthen their maths knowledge fairly quickly before starting their training to become a secondary mathematics teacher.

Course overview

This 24-week fast track course will boost your maths knowledge so that you are able to teach maths up to A Level. To join the Subject Knowledge Enhancement (SKE) course, you should already have received a conditional offer for initial teacher training – or you should at least be considering an application for it.

Typically, you should have already received a conditional offer for initial teacher training (ITT) – or you should at least be considering an application for it. Our course ends in July so that you are ready for ITT in September.

For Home/EU students, there is no tuition fee and you will be paid a bursary while you are studying on the course.

You will cover areas such as geometry, calculus, statistics, mechanics, patterns and equations as well as common errors and misconceptions in mathematics. At the initial interview, we will advise you whether this 24-week fast track course is suitable for you or whether an alternative course would be better for your circumstances.

Once you have successfully completed the SKE course and your initial teacher training, your career prospects will be very good. There is a national shortage of mathematics teachers and there are excellent job prospects, both in the North East and throughout the country.

Reports on our provision by external examiners have been very positive. Comments include: “It is clear that the course remains very successful in preparing candidates appropriately for their subsequent teacher training course”.

Course content

This course enhances your skills and knowledge in mathematics, preparing you for teacher training. You will study the following units:
-Patterns and Equations
-Structure and Pattern
-Development of Geometric Thinking
-Nature of Mathematics
-Investigating Calculus
-Enriching and Strengthening Mathematics
-Elementary Geometry
-Development of Mathematics
-Statistics
-Mechanics
-Using LOGO and 3D Geometry
-Errors and Misconceptions in Mathematics
-Matrices
-Investigating Sequences and Series

Teaching and assessment

We use a wide variety of teaching and learning methods that include lectures, independent work, directed tasks, written assignments and use of ICT. In addition to attending taught sessions, we encourage you to undertake some voluntary work experience in a school. Assessment methods include written work, exams and presentations. We assess all units.

Facilities & location

This course is based on the banks of the River Wear at The Sir Tom Cowie Campus at St Peter’s. Interactive whiteboards are available in our classrooms and we encourage you to use mathematical software, such as Autograph graph-plotting software, to support your learning.

When it comes to IT provision you can take your pick from over a hundred PCs in the St Peter’s Library, a dedicated computer classroom, and wireless access zones. If you have any problems, just ask the friendly helpdesk team.

The University of Sunderland is a vibrant learning environment with a strong international dimension thanks to the presence of students from around the world.

Employment & careers

This course enhances your maths subject knowledge, allowing you to progress on to a teacher training programme such as the University of Sunderland’s PGCE Mathematics Secondary Education and then achieve Qualified Teacher Status.

There is a shortage of mathematics teachers in England so there are excellent career opportunities both in the North East and nationwide.

The starting salary of a Newly Qualified Teacher is over £22,000, with extra if you work in London. Teachers can expect to see their salaries rise by an average of 30 per cent after their first four years in the job.

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This masters is run jointly with Heriot-Watt University. It provides you with expertise in financial mathematics, including stochastic calculus, and a range of practical techniques for analysing financial markets. Read more

Programme description

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

Adding depth to your learning, our work placement programme puts you at the heart of organisations such as Aberdeen Asset Management, Barrie & Hibbert and Lloyds Banking Group.

Programme structure

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

Compulsory courses:

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

Option courses:

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

Career opportunities

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

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Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling. Read more
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling.

We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.

You master these areas through studying topics including:
-Non-linear and evolutionary computational methods for derivatives pricing and portfolio management
-Applications of calculus and statistical methods
-Computational intelligence in finance and economics
-Financial markets

You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

This course is also available on a part-time basis.

Professional accreditation

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.

Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
-HSBC
-Mitsubishi UFJ Securities
-Old Mutual
-Bank of England

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-CCFEA MSc Dissertation
-Financial Engineering and Risk Management
-Introduction to Financial Market Analysis
-Learning and Computational Intelligence in Economics and Finance
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Big-Data for Computational Finance (optional)
-Industry Expert Lectures in Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Programming in Python (optional)
-Artificial Neural Networks (optional)
-High Frequency Finance and Empirical Market Microstructure (optional)
-Machine Learning and Data Mining (optional)
-Trading Global Financial Markets (optional)
-Creating and Growing a New Business Venture (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Constraint Satisfaction for Decision Making (optional)

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

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

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

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

Programme content

Core courses

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

Options

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

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MSc Risk Management & Financial Engineering is a highly quantitative programme tailored to high calibre and technically-minded graduates wanting a deeper, more analytical study of risk management and financial engineering than is found in general finance programmes. Read more
MSc Risk Management & Financial Engineering is a highly quantitative programme tailored to high calibre and technically-minded graduates wanting a deeper, more analytical study of risk management and financial engineering than is found in general finance programmes.

The programme is accredited by the Professional Risk Managers’ International Association (PRMIA) and the School offers students on this programme the opportunity to attend PRMIA events, have access to its resources and receive considerable discounts on PRMIA exams.

The programme

In September you will study five foundation modules to introduce the tools of modern finance and enhance your career development skills. These include:
• Markets and Securities
• Financial Modelling
• Application of Matlab to Finance
• Data Structures and Algorithms using Python
• The Finance Industry

You’ll take eight core modules which are the backbone of our programme, providing you with a solid knowledge base in each subject area. Each module builds on previous experience while introducing new and challenging disciplines. These include:
• Empirical Finance: Methods and Applications
• Financial Engineering
• Financial Statistics
• Investments and Portfolio Management
• Risk Management and Valuation
• Stochastic Calculus

You will also receive training in Visual Basic for Applications (VBA), choose from a variety of electives and undertake a final project. The selection of electives include:
• Advanced Options Theory
• Credit Risk
• Advanced Financial Statistics
• Enterprise Risk Management
• Fixed Income Securities
• International Elective: Macro and Finance for Practitioners
• International Finance
• Insurance
• Structured Credit and Equity Products
• Private Equity and Venture Capital
• Wealth Management and Alternative Investments
• Topics in FinTech Innovation
• Big Data in Finance

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This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. Read more
This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. During the course critical awareness of problems in information transmission, data compression and cryptography is raised, and the mathematical techniques which are commonly used to solve these problems are explored.

The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography and our academic staff include several leading researchers in these areas. Students on the programme have the opportunity to carry out their dissertation projects in cutting-edge research areas and to be supervised by experts.

The transferable skills gained during the MSc will open up a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsofcryptographyandcommunications(msc).aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and a knowledge and understanding of the subjects of cryptography and communications preparing you for research or professional employment in this area.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course former students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses as well as complete a main project under the supervision of a member of staff.

Core courses:
Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed as well as methods for obtaining confidentiality and authentication.

Channels
In this unit, you will investigate the problems of data compression and information transmission in both noiseless and noisy environments.

Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Public Key Cryptography
This course introduces some of the mathematical ideas essential for an understanding of public key cryptography, such as discrete logarithms, lattices and elliptic curves. Several important public key cryptosystems are studied, such as RSA, Rabin, ElGamal Encryption, Schnorr signatures; and modern notions of security and attack models for public key cryptosystems are discussed.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- a suitable mathematical foundation for undertaking research or professional employment in cryptography and/or communications

- the appropriate background in information theory and coding theory enabling them to understand and be able to apply the theory of communication through noisy channels

- the appropriate background in algebra and number theory to develop an understanding of modern public key cryptosystems

- a critical awareness of problems in information transmission and data compression, and the mathematical techniques which are commonly used to solve these problems

- a critical awareness of problems in cryptography and the mathematical techniques which are commonly used to provide solutions to these problems

- a range of transferable skills including familiarity with a computer algebra package, experience with independent research and managing the writing of a dissertation.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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