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The primary aim of this course is to educate you to MSc level in the theoretical and practical aspects of mathematical problem solving, mathematical model development, creating software solutions and communication of results. Read more
The primary aim of this course is to educate you to MSc level in the theoretical and practical aspects of mathematical problem solving, mathematical model development, creating software solutions and communication of results.

This course provides training in the use and development of reliable numerical methods and corresponding software. It aims to train graduates with a mathematical background to develop and apply their skills to the solution of real problems. It covers the underlying mathematical ideas and techniques and the use and design of mathematical software. Several application areas are examined in detail. It develops skills in mathematical problem-solving, scientific computing, and technical communication.

Training is also provided in general computing skills, mathematical typsetting, mathematical writing, desktop and web-based mathematical software development, and the use of computer languages and packages including Mathematica, parallel computing, C#, 3D graphics and animation, and visualisation.

The MSC is now available fully online and can be taken over 12 months full time or 24 months part time.

Visit the website: http://www.ucc.ie/en/ckr36/

Course Details

By the end of the course, you will be able to:

- use the description of a real world problem to develop a reasonable mathematical model in consultation with the scientific literature and possibly experts in the area
- carry out appropriate mathematical analysis
- select or develop an appropriate numerical method and write a computer programme which gives access to a sensible solution to the problem
- present and interpret these results for a potential client or a non-technical audience

Modules

Module descriptions - http://www.ucc.ie/calendar/postgraduate/Masters/science/page05.html#mathematical

AM6001 Introduction to Mathematica (5 credits)
AM6002 Numerical Analysis with Mathematica (5 credits)
AM6003 Cellular Automata (5 credits)
AM6004 Applied Nonlinear Analysis (Computational Aspects) (5 credits)
AM6005 Modelling of Systems with Strong Nonlinearities (5 credits)
AM6006 Mathematical Modelling of Biological Systems with Differential Equations (5 credits)
AM6007 Object Oriented Programming with Numerical Examples (10 credits)
AM6008 Developing Windowed Applications and Web-based Development for Scientific Applications (5 credits)
AM6009 3D Computer Graphics and Animation for Scientific Visualisation (5 credits)
AM6010 Topics in Applied Mathematical Modelling (5 credits)
AM6011 Advanced Mathematical Models and Parallel Computing with Mathematica (5 credits)
AM6012 Minor Dissertation (30 credits)

Format

The course places great emphasis on hands-on practical skills. There is a computer laboratory allocated solely for the use of MSc students. PCs are preloaded with all the required software and tools. Online students are expected to have a suitable PC or laptop available; all required software is provided for installation to faciliate course work. Online teaching hours, involving lecturers, tutorials and practical demonstrations, usually take place in the morninbg. The rest of the time, you are expected to do exercises, assignments and generally put in the time required to acquire key skills.

Assessment

Continuous assessment is the primary method of examining. In each module, typically 40% of the marks are available for take-home assignments and the remaining 60% of marks are examined by a practical computer-based examination. Final projects are read and examined by at least two members of staff.

For more information, please see the Book of Modules 2015/2016 - http://www.ucc.ie/calendar/postgraduate/Masters/science/page05.html#mathematical

Careers

Quantitative graduates with software skills are in high demand in industry according to the Governments Expert Group on Future Skills Needs. Demand for these skills is project to rise over the coming years not just in Ireland but in the EU and globally. Graduates have recently secured jobs in the following areas: banking, financial trading, consultancy, online gambling firms, software development, logistics, data analysis and with companies such as AIB, McAfee, Fexco, DeCare Systems, MpStor, the Tyndall Institute, Matchbook.com, First Derivatives and KPMG.

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. Read more

Mathematical Biology at Dundee

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

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

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

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

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

Aims of the programme

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

Prramme Content

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

A typical selection of taught modules would be:

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

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

Methods of Teaching

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

Taught sessions will be supported by individual reading and study.

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

Career Prospects

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

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

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The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. Read more

Mission and goals

The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. It harmonises a solid scientific background with a command of advanced methodologies and technologies. The programme is characterised by a continuous synergy between Applied Mathematics and Engineering disciplines- The students may choose among three specialisations:
- Computational Science and Engineering
- Applied Statistics
- Quantitative Finance

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Career opportunities

The professional opportunities offered by this course are rather ample and varied: engineering consultancy companies that deal with complex computational problems; manufacturing or civil engineering companies where analyses based on the use of advanced mathematical tools are needed; banks, insurance companies and financial institutions making use of quantitative finance for risk analysis or forecast; companies that require statistical interpretation and the processing of complex data, or the simulation of different scenarios; public and private research institutes and laboratories.

Eligible students

Students holding a Bachelor degree in Mathematical Engineering, or in a related area with a solid background in the core disciplines of the programme, i.e. Applied Mathematics, Computer Science, Applied Physics or other Engineering disciplines are eligible for application. In particular, eligible students' past studies must include courses in different areas of Engineering (among Informatics, Economics & Business Organization, Electrotechnics, Automation, Electronics, Applied Physics, Civil Engineering) for at least 25% of the overall courses, as well as courses in different areas of Mathematics (Mathematical Analysis, Linear Algebra, Geometry, Probability, Statistics, Numerical Analysis, Optimization) for at least 33% of the overall courses.
The following tracks are available:
1. Computational Science and Engineering
2. Applied Statistics
3. Quantitative Finance

Eligible students must clearly specify the track they are applying for in their motivation letter.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Mathematical_Engineering.pdf
The Master of Science in Mathematical Engineering (MSME) aims to form an innovative and flexible professional profile, endowed with a wide spectrum of basic scientific notions and engineering principles, together with a deep knowledge of modern pure and applied mathematical techniques. MSME is characterized by a continuous synergy between Mathematics and Engineering methods, oriented to the modelling, analysis and solution of complex planning, control and management problems, and provides the students with the possibility to face problems from various scientific, financial and/or technological areas. The MSME graduates can find employment in Engineering companies specialized in handling complex computational problems, requiring a multidisciplinary knowledge; in companies manufacturing industrial goods for which design analysis based on the use of advanced mathematical procedures are required; in service societies, banks, insurance companies, finance or consultant agencies for the statistical interpretation and the simulation of complex situations related to the analysis of large number of data (e.g. management and optimization of services, data mining, information retrieval) or for handling financial products and risk management; in public and private institutions. The programme is taught in English.

Subjects

Three main tracks available:
1. Computational Science for Engineering
Real and functional analysis; algorithms and parallel programming; numerical and theoretical analysis for partial differential equations; fluid mechanics; computational fluid dynamics advanced programming techniques for scientific computing;

2. Statistics
Real and functional analysis; algorithms and parallel programming; stochastic dynamical models; applied statistics, model identification and data analysis; Bayesian statistics

3. Mathematical Finance
Real and functional analysis; algorithms and parallel programming; stochastic differential equations; mathematical finance; financial engineering; model identification and data analysis.

In the motivation letter the student must clearly specify the track he/she is applying for.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

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In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. Read more
In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.
The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, Complexity Theory, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.
Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

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

Admission requirements for international students

1. A completed Bachelor's degree in Mathematics or Computer Science
In order to get admission to this Master’s you will need a completed Bachelor's in mathematics or computer science that have a strong mathematical background and theoretical interests. We will select students based on their motivation and their background. Mathematical maturity is essential and basic knowledge of logic and discrete mathematics is expected.

2. A proficiency in English
In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:
- TOEFL score of ≥575 (paper based) or ≥90 (internet based)
- IELTS score of ≥6.5
- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

There is a serious shortage of well-trained information specialists. Often students are offered a job before they have actually finished their study. About 20% of our graduates choose to go on to do a PhD but most find jobs as systems builders, ICT specialists or ICT managers in the private sector or within government.

Our approach to this field

In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.

The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, General Topology, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.

Our research in this field

Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

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

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The MSc in Mathematical Trading & Finance prepares you for the sophisticated new investment opportunities, risks and instruments created by financial innovation and globalisation. Read more
The MSc in Mathematical Trading & Finance prepares you for the sophisticated new investment opportunities, risks and instruments created by financial innovation and globalisation.

The programme combines mathematical theory with practical applications, teaching you how to control risks and understand the complex structure of derivative securities. Students should be at ease with sophisticated mathematical methods and statistical techniques.

By the end of the course you will be ready to participate in derivatives markets, and many graduates have progressed directly to trading floor positions in leading banks. Cass's proximity to the City of London has done much to facilitate this progression, Cass's Bloomberg and Thomson Reuters trading rooms, which expertly simulate the trading environment, also do much to prepare you for the real world.

The Masters in Mathematical Trading and Finance was launched with the generous support of the Corporation of London.

Visit the website: http://www.cass.city.ac.uk/courses/masters/courses/mathematical-trading-and-finance

Course detail

The MSc in Mathematical Trading & Finance starts with two compulsory induction weeks, mainly dedicated to:

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

• a refresher course of advanced financial mathematics, statistics, computing and electronic databases

Format

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

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

Assessment

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

Career opportunities

There is a continuous demand for capable postgraduate level executives in the world of finance.

Graduates from the MSc in Mathematical Trading & Finance move into a range of careers in the financial sector in particular careers in trading are popular with our alumni.

Some examples of where graduates from the MSc in Mathematical Trading & Finance class of 2014 are working are:

• Accenture - Management Consultant
• Wipro - Business Analyst
• Regione Lombardia - Economic Consultant
• Ice Clear Europe - Junior Risk Analyst

How to apply

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

Funding

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

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The MSc Mathematical Medicine and Biology will provide you with skills suitable for a research career in the exciting and growing field of mathematical medicine and biology. Read more

Overview

The MSc Mathematical Medicine and Biology will provide you with skills suitable for a research career in the exciting and growing field of mathematical medicine and biology.

You will take core modules in biology and the application of mathematics to medicine and biology. More advanced modules will introduce research topics in biomedical mathematics, including options in Computational Biology and Theoretical Neuroscience.

The taught training programme will be followed by a substantial individual project leading to a dissertation.

Throughout the course, the exceptional strength of the Centre for Mathematical Medicine and Biology will facilitate your hands-on experience of interdisciplinary biomedical research.

Some teaching activities will take place at the Sutton Bonington campus. The University provides a regular free hopper bus between University Park and Sutton Bonington.

Key facts:

- This course is informed by the work being carried out in the Centre for Mathematical Medicine and Biology.

- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.

- In the latest independent Research Assessment Exercise, the school ranked eighth 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).

Module details

Biomolecular Data and Networks

Cell Structure and Function for Engineers

Computational and Systems Biology

Mathematical Medicine and Biology

Mathematical Medicine and Biology Dissertation

Practical Biomedical Modelling

Theoretical Neuroscience

Topics in Biomedical Mathematics

English language requirements for international students

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

Further information



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Most things in the real world are complex and difficult to understand, from biological systems to the financial markets to industrial processes, but explaining them is essential to making progress in the modern world. Read more
Most things in the real world are complex and difficult to understand, from biological systems to the financial markets to industrial processes, but explaining them is essential to making progress in the modern world. Mathematical modelling is a fundamental tool in the challenge to understand many of these systems, and is an essential part of contemporary applied mathematics. By developing, analysing and interpreting mathematical and computational models we gain insight into these complex processes, as well as giving a framework in which to interpret experimental data.

To fully capitalise on these tools, there is a fundamental need in both academic research and industry for a new generation of scientists trained to work at the interdisciplinary frontiers of mathematics and computation. These scientists require the ability to assimilate and understand information from other disciplines, communicate with and enthuse other researchers, as well as having the advanced mathematical and computational skills needed.

MSc Mathematical Modelling is a one year master’s level course at the interfaces of Mathematics, Computer Science, Systems Biology and Chemical Engineering. Interdisciplinary mathematical modelling in the School of Mathematics at the University of Birmingham takes place in a thriving outward-facing community with specialities including mathematical biology, fluid mechanics, mathematical finance and industrial modelling. The School collaborates widely with multiple disciplines, including Biological and Medical Sciences, Chemical Engineering and within industry. In particular, Birmingham is an emerging centre for multidisciplinary Biological Systems Science research, and is in a unique position, being adjacent to one of the largest super-hospitals in Europe, catering for a highly diverse population.

The programme is specifically tailored to develop students from a strong mathematics background into becoming genuinely multidisciplinary scientists. You will have the opportunity to develop your mathematical and computational modelling skills, whilst at the same time being trained in cutting-edge interdisciplinary techniques, including the option of practical work. You will learn how to diversify your skills into other fields, and how to work with research leaders and other students from different disciplines.

About the School of Mathematics

The School of Mathematics is one of seven schools in the College of Engineering and Physical Sciences. The school is situated in the Watson Building on the main Edgbaston campus of the University of Birmingham. There are about 50 academic staff, 15 research staff, 10 support staff, 60 postgraduate students and 600 undergraduate students.
At the School of Mathematics we take the personal development and careers planning of our students very seriously. Jointly with the University of Birmingham's Careers Network we have developed a structured programme to support maths students with their career planning from when they arrive to when they graduate and beyond.

Funding and Scholarships

There are many ways to finance your postgraduate study at the University of Birmingham. To see what funding and scholarships are available, please visit: http://www.birmingham.ac.uk/postgraduate/funding

Open Days

Explore postgraduate study at Birmingham at our on-campus open days.
Register to attend at: http://www.birmingham.ac.uk/postgraduate/visit

Virtual Open Days

If you can’t make it to one of our on-campus open days, our virtual open days run regularly throughout the year. For more information, please visit: http://www.pg.bham.ac.uk

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This MSc provides an ideal foundation for students wishing to advance their mathematical modelling skills. The programme teaches students the basic concepts which arise in a broad range of technical and scientific problems and illustrates how these may be applied in a research context to provide powerful solutions. Read more
This MSc provides an ideal foundation for students wishing to advance their mathematical modelling skills. The programme teaches students the basic concepts which arise in a broad range of technical and scientific problems and illustrates how these may be applied in a research context to provide powerful solutions.

Degree information

Students develop an understanding of the processes undertaken to arrive at a suitable mathematical model and are taught the fundamental analytical techniques and computational methods used to develop insight into system behaviour. The programme introduces a range of problems - industrial, biological and environmental - and associated conceptual models and solutions.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits), and a research dissertation (60 credits). The part-time option normally spans two years. The eight taught modules are spread over the two years. The research dissertation is taken in the summer of the second year.

Core modules
-Advanced Modelling Mathematical Techniques
-Nonlinear Systems
-Operational Research
-Computational and Simulation Methods
-Frontiers in Mathematical Modelling and its Applications

Optional modules
-Asymptotic Methods & Boundary Layer Theory
-Biomathematics
-Cosmology
-Evolutionary Game Theory and Population Genetics
-Financial Mathematics
-Geophysical Fluid Dynamics
-Mathematical Ecology
-Quantitative and Computational Finance
-Real Fluids
-Traffic Flow
-Waves and Wave Scattering

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of approximately 15,000-words and a project presentation.

Teaching and learning
The programme is delivered through seminar-style lectures and problem and computer-based classes. Student performance is assessed through a combination of unseen examination and coursework. For the majority of courses, the examination makes up between 90–100% of the assessment. The project is assessed through the dissertation and an oral presentation.

Careers

Our graduates have found employment in a wide variety of organisations such as Hillier-Parker, IBM, Swissbank, Commerzbank Global Equities, British Gas, Harrow Public School, Building Research Establishment and the European Centre for Medium-Range Weather-Forecasting. First destinations of recent graduates include:
-R.T.E: Engineer
-Tower Perrins: Actuarist
-Deloitte: Quantitative Analyst
-UCL: Research Associate
-C-View: Quantitative Trader
-One-to-One: Maths Tutor
-UCL Research Degree - Mathematics
-Duff & Phelps Ltd: Financial Engineer
-Bank of Tokyo Mitsubishi: Assistant Compliance Officer

Employability
The finance, actuarial and accountancy professionals are constantly in demand for high-level mathematical skills and recent graduates have taken positions in leading finance-related companies such as UBS, Royal Bank of Scotland, Societe Generale, PricewaterhouseCoopers, Deloitte, and KPMG.

In the engineering sector, recent graduates from the MSc include a mathematical modeller at Steet Davies Gleave, a leading Transportation Planning Consultancy; and a graduate trainee at WesternGreco, a business segment of Schlumberger that provides reservoir imaging, monitoring, and development services. In addition, a number of graduates have remained in education either progressing to a PhD or entering the teaching profession.

Why study this degree at UCL?

UCL Mathematics is internationally renowned for its excellent individual and group research that involves applying modelling techniques to problems in industrial, biological and environmental areas.

The department hosts a stream of distinguished international visitors. In recent years four staff members have been elected fellows of the Royal Society, and the department publishes the highly regarded research journal Mathematika.

This MSc enables students to consolidate their mathematical knowledge and formulate basic concepts of modelling before moving on to case studies in which models have been developed for issues motivated by industrial, biological or environmental considerations.

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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 School of Mathematics and Alliance Manchester Business School at the University of Manchester have combined their academic strength and practical expertise to deliver the MSc in Mathematical Finance (UK 1 year), ensuring that students can experience both the mathematical and economic perspective of the subject. Read more
The School of Mathematics and Alliance Manchester Business School at the University of Manchester have combined their academic strength and practical expertise to deliver the MSc in Mathematical Finance (UK 1 year), ensuring that students can experience both the mathematical and economic perspective of the subject.

This is also supported by invited lectures from senior staff members of leading financial institutions and outstanding mathematicians who are internationally recognised for contributions to Mathematical Finance. Past lectures include:
-Professor M. Schweizer (ETH Zurich and Swiss Finance Institute) An overview of quadratic hedging and related topics
-Professor H. Follmer (Humboldt University of Berlin) Monetary valuation of cash flows under Knightian uncertainty
-Professor M. H. A. Davis (Imperial College London) Contagion models in credit risk

The course provides students with advanced knowledge and understanding of the main theoretical and applied concepts in Mathematical Finance delivered from a genuinely international and multi-cultural perspective with a current issues approach to teaching. The focus is on mathematical theory and modelling, drawing from the disciplines of probability theory, scientific computing and partial differential equations to derive relations between asset prices and interest rates, and to develop models for pricing, risk management and financial product development.

The finance industry demands recruits with strong quantitative skills and the course is intended to prepare students for careers in this area. The course provides training for those who seek a career in the finance industry specialising in derivative securities, investment, risk management and hedge funds. It also provides research skills for those who subsequently wish to pursue research and/or an academic career (e.g. university lecturer) or continue the study at doctoral level, particularly those wishing to pursue further/advanced studies in Mathematical Finance.

Coursework and assessment

Teaching is shared by the School of Mathematics and Alliance Manchester Business School, and delivered through lectures, case studies, seminars and group project-based work.

Career opportunities

The finance industry demands recruits with strong quantitative skills and the course is intended to prepare students for careers in this area. The course provides training for those who seek a career in the finance industry specialising in derivative securities, investment, risk management and hedge funds. It also provides research skills for those who subsequently wish to pursue research and/or an academic career (e.g. university lecturer) or continue the study at doctoral level, particularly those wishing to pursue further/advanced studies in Mathematical Finance.

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Students take modules in Mathematical Physics and Mathematics. At least 4 of the modules (at least 45 ECTS) must be taken at the Masters level (level 6 in Mathematical Physics and level 5 in Mathematics). Read more

Overview

Students take modules in Mathematical Physics and Mathematics. At least 4 of the modules (at least 45 ECTS) must be taken at the Masters level (level 6 in Mathematical Physics and level 5 in Mathematics). The remaining credits may be made up at levels 4, 5 or 6.

See the website https://www.maynoothuniversity.ie/mathematical-physics/our-courses/msc-mathematical-science-pt

Course Structure

All module choices are subject to the approval of the Head of Department. Level 6 choices for Mathematical Physics are listed below. For other choices see the Mathematics Department modules at level 5 (see MSc in Mathematics MHR52) and Mathematical Physics Department modules at level 4. One of the Masters level modules may be replaced by a minor thesis subject to the approval of the Head of Department. Total credits 60. Modules include Groups, Geometry and Topology for Physics, Quantum Field Theory, Differential Geometry, General Relativity, and advanced special topics in Applied Mathematics and Theoretical Physics.

Career Options

The course provides a solid foundation in Theoretical Physics/Applied Mathematics/Pure Mathematics for students who wish to pursue careers in science, engineering, commerce and technology. Graduates gain employment in a wide range of occupations including research, teaching, actuary, banking, software development, computational physics and computer modelling/simulation. Students who perform well may go on to the PhD programme.

How To Apply

Online application only http://www.pac.ie/maynoothuniversity

PAC Code
MHQ53

The following information should be forwarded to PAC, 1 Courthouse Square, Galway or uploaded to your online application form:

Certified copies of all official transcripts of results for all non-Maynooth University qualifications listed MUST accompany the application. Failure to do so will delay your application being processed. Non-Maynooth University students are asked to provide two academic references and a copy of birth certificate or valid passport.

Find information on Scholarships here https://www.maynoothuniversity.ie/study-maynooth/postgraduate-studies/fees-funding-scholarships

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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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This programme is aimed at graduates whose level of mathematical training is high, but below that of the BSc Degree Honours in Mathematics or Mathematical Physics, and who have demonstrated mathematical flair. Read more
This programme is aimed at graduates whose level of mathematical training is high, but below that of the BSc Degree Honours in Mathematics or Mathematical Physics, and who have demonstrated mathematical flair. It enables them to reach in one year a level of mathematical knowledge equivalent to that of BSc Honours graduates and thus, in particular, qualifies them to enter the MSc degree in Mathematics, Mathematical Physics or Mathematical Sciences.

Students in the programme choose one of two streams:

The Applied and Computational Mathematics Stream
The Mathematics Stream

The programme extends over two semesters and involves 60 credits of taught modules.

This programme runs full time for one academic year - September to May (2 semesters)
This programme runs part time for two academic years - September to May (4 semesters)

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From geometry, analysis, partial differential equations and mathematical physics to fluid dynamics, meteorology and modelling in life sciences – our Masters in Mathematics offers you an extraordinary range of research opportunities that lie at the heart of tackling the key scientific questions of our age. Read more
From geometry, analysis, partial differential equations and mathematical physics to fluid dynamics, meteorology and modelling in life sciences – our Masters in Mathematics offers you an extraordinary range of research opportunities that lie at the heart of tackling the key scientific questions of our age.

PROGRAMME OVERVIEW

This programme reflects and benefits from the strong research activities of the Department of Mathematics.

The taught modules and dissertation topics are closely aligned with the interests of the Department’s four research groups:
-Mathematics of Life and Social Sciences
-Dynamical Systems and Partial Differential Equations
-Fields, Strings and Geometry
-Fluids, Meteorology and Symmetry

During the first two semesters you will take a range of taught modules from an extensive list of options, followed by an extended research project conducted over the summer under the supervision of a member of the department, culminating in the writing of a dissertation.

PROGRAMME STRUCTURE

This programme is studied full-time over one academic year. It consists of eight taught modules and a dissertation. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Maths of Weather
-Graphs and Networks
-Manifolds and Topology
-Quantum Mechanics
-Numerical Solutions of PDEs
-Functional Analysis and Partial Differential Equations
-Nonlinear Wave Equations
-Representation Theory
-Advanced Techniques in Mathematics
-Lie Algebras
-Nonlinear Patterns
-Geometric Mechanics
-Relativity
-Ecological and Epidemiological Modelling
-Mathematical Biology and Physiology
-Topology
-Non-Commutative Algebra
-Dissertation

CAREERS

Mathematics is not only central to science, technology and finance-related fields, but the logical insight, analytical skills and intellectual discipline gained from a mathematical education are highly sought after in a broad range of other areas such as law, business and management.

There is also a strong demand for new mathematics teachers to meet the ongoing shortage in schools.

As well as being designed to meet the needs of future employers, our MSc programme also provides a solid foundation from which to pursue further research in mathematics or one of the many areas to which mathematical ideas and techniques are applied.

EDUCATIONAL AIMS OF THE PROGRAMME

-To provide graduates with a strong background in advanced mathematical theory and its applications to the solution of real problems
-To develop students understanding of core areas in advanced mathematics including standard tools for the solution of real life applied mathematical problems
-To develop the skill of formulating a mathematical problem from a purely verbal description
-To develop the skill of writing a sophisticated mathematical report and, additionally, in presenting the results in the form of an oral presentation
-To lay a foundation for carrying out mathematical research leading to a research degree and/or a career as a professional mathematician in an academic or non-academic setting

PROGRAMME LEARNING OUTCOMES

Knowledge and understanding
-Knowledge of the core theory and methods of advanced pure and applied mathematics and how to apply that theory to real life problems
-An in-depth study of a specific problem arising in a research context

Intellectual / cognitive skills
-Ability to demonstrate knowledge of key techniques in advanced mathematics and to apply those techniques in problem solving
-Ability to formulate a mathematical description of a problem that may be described only verbally
-An understanding of possible shortcomings of mathematical descriptions of reality
-An ability to use software such as MATLAB and IT facilities more generally including research databases such as MathSciNet and Web of Knowledge

Professional practical skills
-Fluency in advanced mathematical theory
-The ability to interpret the results of the application of that theory
-An awareness of any weaknesses in the assumptions being made and of possible shortcomings with model predictions
-The skill of writing an extended and sophisticated mathematical report and of verbally summarising its content to specialist and/or non-specialist audiences

Key / transferable skills
-Ability to reason logically and creatively
-Effective oral presentation skills
-Written report writing skills
-Skills in independent learning
-Time management
-Use of information and technology

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

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The MSc in Computational Mathematical Finance (CMF) is a dynamic new programme with the aim to deliver high quality training in the theory of Mathematical Finance with strong emphasis on computational methods. Read more

Programme description

The MSc in Computational Mathematical Finance (CMF) is a dynamic new programme with the aim to deliver high quality training in the theory of Mathematical Finance with strong emphasis on computational methods.

Currently graduates in this field are expected to have a working knowledge of advanced computational finance (including construction of algorithms and programming skills) as well as a sound knowledge of the theory of Probability and Stochastic Analysis. These are the core theories needed in the modern valuation of complex financial instruments.

This MSc programme delivers:

a flexible programme of study relevant to the needs of employers such as: top investment banks, hedge funds and asset management firms
a solid knowledge in financial derivative pricing, risk management and portfolio management
the transferable computational skills required by the modern quantitative finance world

Programme structure

You must obtain a total of 180 credits to be awarded the MSc. Over semesters 1 and 2, you will take compulsory courses worth a total of 85 credits and optional courses worth a further 35 credits. Successful performance in these courses (assessed through coursework or examinations or both) allows you to start work on a three-month dissertation project, worth 60 credits, for the award of the MSc degree.

There are two streams: the Financial stream and the Computational stream.

Compulsory courses (both streams):

Stochastic Analysis in Finance (20 credits, semester 1)
Discrete-Time Finance (10 credits, semester 1)
Finance, Risk and Uncertainty (10 credits, semester 1)
Object-Oriented Programming with Applications (10 credits, semester 1)
Risk-Neutral Asset Pricing (10 credits, semester 2)
Stochastic Control and Dynamic Asset allocation (10 credits, semester 2)
Monte Carlo Methods (5 credits, semester 2)
Research-Linked Topics (10 credits, semesters 1 and 2)

Optional courses - Computational stream:

Numerical Methods for Stochastic Differential Equations [compulsory] (5 credits, semester 2)
Numerical Partial Differential Equations [compulsory] (10 credits, semester 2)
Programming Skills - HPC MSc (10 credits, semester 1)
Parallel Numerical Algorithms - HPC MSc (10 credits, semester 1)

Optional courses - Financial stream:

Financial Risk Theory [compulsory] (10 credits, semester 2)
Optimization Methods in Finance [compulsory] (10 credits, semester 2)
Advanced Time Series Econometrics (10 credits, semester 2)
Credit Scoring (10 credits, semester 2)
Computing for Operational Research and Finance (10 credits, semester 1)
Financial Risk Management (10 credits, semester 2)
Stochastic Optimization (5 credits, semester 2)

Learning outcomes

At the end of this programme you will have:

developed personal communications skills, initiative, and professionalism within a mathematical context
developed transferable skills that maximise your prospects for future employment, including writing, oral presentation, team-working, numerical and logical problem-solving, planning and time-management
improved your ability to convey ideas in an articulate fashion, to build upon previous mathematical training and further develop logic and deductive skills
mastered standard and advanced mathematical tools used to solve applied problems relevant to the mathematical finance industry
developed quantitative and computational skills for the proficient fulfilment of tasks in the financial sector

Career opportunities

Graduates can expect to go on to work in major financial institutions or to continue their studies by joining PhD programmes.

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