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Masters Degrees (Dynamical Systems)

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This course will provide the knowledge and skills required of a professional engineer to design advanced control systems for complex dynamical systems. Read more
This course will provide the knowledge and skills required of a professional engineer to design advanced control systems for complex dynamical systems. The course includes advanced modules on dynamical systems and control theory and also covers the latest techniques for implementing these technologies on a range of high-performance applications.

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If you have a mathematical background and want to apply your mathematical skills to understanding the complex behaviour of the Earth’s atmosphere and oceans then this could be the programme for you. Read more

If you have a mathematical background and want to apply your mathematical skills to understanding the complex behaviour of the Earth’s atmosphere and oceans then this could be the programme for you. This is an exciting interdisciplinary subject, of increasing importance to a society facing climate change.

You’ll be trained in both modern applied mathematics and atmosphere-ocean science, combining teaching resources from the School of Mathematics and the School of Earth and Environment. The latter are provided by members of the School’s Institute for Climate and Atmospheric Science, part of the National Centre for Atmospheric Science.

Only a handful of UK universities are positioned to offer similar interdisciplinary training in modern applied mathematics and atmosphere-ocean-climate science.

If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.

Course content

The focus of the course is on analysing the equations of fluid dynamics and thermodynamics, via mathematical and numerical modelling. The programme is highly flexible, meaning you are free to choose options from applied maths, atmosphere-ocean science, numerical methods and scientific computation alongside the compulsory core applied maths and fluid dynamics modules.

Topics are drawn from four broad areas:

  1. Applied mathematics: asymptotic methods, fluid dynamics, mathematical theory of waves and stability of flow
  2. Numerical methods and computing: discretization of ordinary and partial differential equations, algorithms for linear algebra, direct use of numerical weather and climate models
  3. Atmospheric dynamics: structure of the atmosphere, dynamics of weather systems and atmospheric waves
  4. Ocean dynamics: the large-scale ocean circulation, surface waves and tides

Modules are taught either by the School of Mathematics or the School of Earth and Environment.

The course is made up of two parts: a set of taught modules, and a research project. Two-thirds of the course consists of taught modules involving lectures and some computer workshops. Beyond a compulsory core of atmosphere-ocean fluid dynamics, students may choose options to suit their interests from applied maths (e.g. nonlinear dynamics), atmosphere-ocean science (e.g. climate change processes, weather forecasting), numerical methods and scientific computation. The final third of the course consists of an intensive summer project, in which students conduct an in-depth investigation of a chosen subject related to the course.

Course structure

Compulsory modules

  • Dissertation in Mathematics 60 credits

Optional modules

  • Scientific Computation 15 credits
  • Mathematical Methods 15 credits
  • Linear and Non-Linear Waves 15 credits
  • Hydrodynamic Stability 15 credits
  • Dynamical Systems 15 credits
  • Nonlinear Dynamics 15 credits
  • Analytic Solutions of Partial Differential Equations 15 credits
  • Introduction to Entropy in the Physical World 15 credits
  • Astrophysical Fluid Dynamics 15 credits
  • Numerical Methods 10 credits
  • Modern Numerical Methods 15 credits
  • Fluid Dynamics 2 15 credits
  • Advanced Mathematical Methods 20 credits
  • Advanced Linear and Nonlinear Waves 20 credits
  • Advanced Hydrodynamic Stability 20 credits
  • Advanced Dynamical Systems 20 credits
  • Advanced Nonlinear Dynamics 20 credits
  • Advanced Entropy in the Physical World 20 credits
  • Foundations of Fluid Dynamics 30 credits
  • Advanced Geophysical Fluid Dynamics 20 credits
  • Advanced Astrophysical Fluid Dynamics 20 credits
  • Advanced Modern Numerical Methods 20 credits
  • Independent Learning and Skills Project 15 credits
  • Atmosphere and Ocean Climate Change Processes 10 credits
  • Practical Weather Forecasting 10 credits
  • Dynamics of Weather Systems 15 credits
  • Weather, Climate and Air Quality 30 credits
  • Environmental Modelling 15 credits
  • Advanced Atmosphere and Ocean Dynamics 15 credits

For more information on typical modules, read Atmosphere-Ocean Dynamics MSc in the course catalogue

Learning and teaching

Teaching is by lectures, tutorials, practical classes, and one-on-one supervision (for research projects). Outside these formal sessions, students are able to study at their own pace, aided by our wide range of electronic teaching resources.

Assessment

Assessment is by course work and written exams which take place at the end of the semester in which the module is taught.

Career opportunities

Students will be prepared for postgraduate research in applied mathematics or atmosphere-ocean science, or employment in the environmental sector.

However, given the interdisciplinary nature of the programme, graduates will have expertise and skills in a number of different areas, and should be attractive to a wide range of employers.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.



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The Applied Mathematics group in the School of Mathematics at the University of Manchester has a long-standing international reputation for its research. Read more
The Applied Mathematics group in the School of Mathematics at the University of Manchester has a long-standing international reputation for its research. Expertise in the group encompasses a broad range of topics, including Continuum Mechanics, Analysis & Dynamical Systems, Industrial & Applied Mathematics, Inverse Problems, Mathematical Finance, and Numerical Analysis & Scientific Computing. The group has a strongly interdisciplinary research ethos, which it pursues in areas such as Mathematics in the Life Sciences, Uncertainty Quantification & Data Science, and within the Manchester Centre for Nonlinear Dynamics.

The Applied Mathematics group offers the MSc in Applied Mathematics as an entry point to graduate study. The MSc has two pathways, reflecting the existing strengths within the group in numerical analysis and in industrial mathematics. The MSc consists of five core modules (total 75 credits) covering the main areas of mathematical techniques, modelling and computing skills necessary to become a modern applied mathematician. Students then choose three options, chosen from specific pathways in numerical analysis and industrial modelling (total 45 credits). Finally, a dissertation (60 credits) is undertaken with supervision from a member of staff in the applied mathematics group with the possibility of co-supervision with an industrial sponsor.

Aims

The course aims to develop core skills in applied mathematics and allows students to specialise in industrial modelling or numerical analysis, in preparation for study towards a PhD or a career using mathematics within industry. An important element is the course regarding transferable skills which will link with academics and employers to deliver important skills for a successful transition to a research career or the industrial workplace.

Special features

The course features a transferable skills module, with guest lectures from industrial partners. Some dissertation projects and short internships will also be available with industry.

Teaching and learning

Students take eight taught modules and write a dissertation. The taught modules feature a variety of teaching methods, including lectures, coursework, and computing and modelling projects (both individually and in groups). The modules on Scientific Computing and Transferable Skills particularly involve significant project work. Modules are examined through both coursework and examinations.

Coursework and assessment

Assessment comprises course work, exams in January and May, followed by a dissertation carried out and written up between June and September. The dissertation counts for 60 credits of the 180 credits and is chosen from a range of available projects, including projects suggested by industrial partners.

Course unit details

CORE (75 credits)
1. Mathematical methods
2. Partial Differential Equations
3. Scientific Computing
4. Dynamical Systems
5. Transferrable skills for mathematicians

Industrial modelling pathway
1 Continuum mechanics
2. Stability theory
3. Conservation and transport laws

Numerical analysis pathway
1. Numerical linear algebra
2. Finite Elements
3. Optimization and variational calculus

Career opportunities

The programme will prepare students for a career in research (via entry into a PhD programme) or direct entry into industry. Possible subsequent PhD programmes would be those in mathematics, computer science, or one of the many science and engineering disciplines where applied mathematics is crucial. The programme develops many computational, analytical, and modelling skills, which are valued by a wide range of employers. Specialist skills in scientific computing are valued in the science, engineering, and financial sector.

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Our MSc in Mathematical Sciences is a flexible and challenging programme, taught by leading experts in the field. It allows you to develop a wide range of mathematical techniques and gives you a solid foundation to progress to research and employment at the highest levels. Read more
Our MSc in Mathematical Sciences is a flexible and challenging programme, taught by leading experts in the field. It allows you to develop a wide range of mathematical techniques and gives you a solid foundation to progress to research and employment at the highest levels.

Under the guidance of an academic mentor, you will be offered a choice of units spanning the breadth of mathematics. The programme offers a huge variety of possible combinations of units and themes, allowing you to add units from other schools to create an MSc which matches your interests. Its taught element is followed in June by your chosen research project, which is supervised by an experienced research academic.

The programme gives you the opportunity to increase your understanding of mathematical theory and equips you with fundamental skills in the modelling and analysis of problems. Our graduates are highly sought-after by employers for their strong analytical, communication and organisational skills.

Programme structure

Structure
The MSc in Mathematical Sciences comprises a taught component of 120 credit points (October to May), followed by a 60-credit research project (June to September).

Units
There is an extensive range of possible combinations of units and themes. An academic mentor will advise you on these units and meet regularly with you individually or in small groups throughout the taught component. You are also invited to participate in the wider academic life of the school, including research seminars.

Research project
Research themes include:
-Algebra and Representation Theory
-Applied Probability in Biology and Communications
-Bayesian Modelling and Analysis
-Dynamical systems and Statistical Mechanics
-Ergodic Theory and Dynamical Systems
-Fluid Dynamics
-Geometric Analysis
-Logic and Set Theory
-Material Science
-Monte Carlo Methods
-Nonparametric Regression
-Number Theory
-Probability: Scaling limits and Statistical Physics
-Quantum Information
-Quantum Chaos
-Random Matrix Theory
-Time Series and Finance

Careers

This programme provides you with quantitative research, reasoning and problem solving skills that will be valuable in your future career. Mathematics graduates find employment in finance, accountancy, research, teaching and management.

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How does a bank check whether your digital signature is a valid one? Do planets move in stable orbits or will they eventually collide? How can a 3D-sphere within the 3D-figures be characterized?. Read more
How does a bank check whether your digital signature is a valid one? Do planets move in stable orbits or will they eventually collide? How can a 3D-sphere within the 3D-figures be characterized?

The mathematics behind these questions is dealt with in the Master's degree programme in Mathematics. The objective of the Master's degree in Mathematics is to teach you the mathematical knowledge, skills and attitude needed to pursue a professional (research) career.

You will gain specialized mathematical knowledge in selected areas such as algebra and geometry, dynamical systems and analysis, and statistics probability theory. Furthermore, you will learn how to solve a problem by using abstraction and modelling and to find scientific literature on the subject. You will be able to determine whether the problem can be solved by using existing mathematical theory or whether new theory should be developed. Finally, you will learn how to present mathematical results in written and oral form, for both specialized and general audiences.

The Master's programme in Mathematics offers four specialisations:
* Algebra and Geometry
* Dynamical Systems and Analysis
* Statistics and Probability
* Science, Business and Policy

Why in Groningen?

- For a career in science or a company
- Acquire skills highly appreciated by employers
- Informal community, small classes

Job perspectives

A Master's degree in Mathematics opens up many job opportunities. During the Master's programme, you will learn to think in a logical, systematic and problem-oriented way. These qualities are highly appreciated by employers. If you want to work in a company you can find employment at, for instance, banks, insurance companies, the consultancy branch and research and development departments of companies like Philips, TNO, Gasunie, Ericsson and LogicaCMG.

You can start a scientific career as a PhD student at a university. This means working for four years on a research project and writing a thesis. After successfully defending this thesis, you will be awarded a PhD degree. Afterwards you can continue your career at a university or start a career in a company.

Job examples

- Work for multinationals such as TNO and Philips
- Start an academic career
- Analyst at bank or insurance company
- Consultant

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

Program overview

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

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

Curriculum

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

See website for individual module details.

Other entry requirements

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

Additional information

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

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

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

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

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Whether you are interested in pursuing an MSc or PhD degree, we have much to offer. Our faculty include internationally renowned scholars in Computer Algebra, Dynamical Systems, Mathematical Biology, High-Energy Physics, and Soft-Matter Physics. Read more
Whether you are interested in pursuing an MSc or PhD degree, we have much to offer. Our faculty include internationally renowned scholars in Computer Algebra, Dynamical Systems, Mathematical Biology, High-Energy Physics, and Soft-Matter Physics. We also offer collaborative graduate degrees in Theoretical Physics, and Scientific Computing.

Upon completion, our graduates work in a variety of academic institutions, government agencies, and private businesses around the world.

Visit the website: http://grad.uwo.ca/prospective_students/programs/program_NEW.cfm?p=11

Fields of Research

• Biological and Materials Physics
• Mathematical Biology and Dynamical Systems
• Symbolic Computation and Differential Equations
• Theoretical Physics

Times to Completion

• Six terms (two years)

Curriculum Options

• Full-time study
• Thesis-based
• Course-based

How to apply

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

Financing your studies

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

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This one year taught postgraduate programme leads to the degree of MSc in Pure Mathematics and Mathematical Logic. Read more
This one year taught postgraduate programme leads to the degree of MSc in Pure Mathematics and Mathematical Logic. The programme is suitable not only for students who wish to improve their background knowledge prior to applying to undertake a PhD by research, but also for students who wish to enhance their knowledge of postgraduate-level abstract mathematics.

The MSc comprises of the taught component, running from the start of the academic year in September until the end of the second semester in late Spring, followed by the dissertation component running from May until September.

During the taught component of the course, you will normally take five units together with a written project. You may choose exclusively pure topics, exclusively logic topics, or, a mixture of both. The project is normally an expository account of a piece of mathematics and you will write this under the guidance of a supervisor. The taught component comprises of conventional lectures supported by examples classes, project work and independent learning via reading material.

After successfully completing the taught component, you will prepare a dissertation on an advanced topic in pure mathematics or mathematical logic, normally of current or recent research interest, chosen in consultation with your supervisor.

You can also take the programme part-time, over a period of two years. There is some flexibility in the precise arrangements for this programme, but you would normally attend two lecture courses each semester for three semesters before commencing work on your dissertation.

Aims

The aims of the programme are to provide training in a range of topics related to pure mathematics and mathematical logic, to encourage a sophisticated and critical approach to mathematics, and to prepare students who have the ability and desire to follow careers as professional mathematicians and logicians in industry or research.

Coursework and assessment

The taught component is assessed by coursework, project work and by written examination. The written exams take place at the end of January (for the first semester course units) and the end of May (for the second semester course units). The dissertation component is assessed by the quality and competence of the written dissertation.

The Postgraduate Diploma and Postgraduate Certificate exist as exit awards for students who do not pass at MSc level.

Course unit details

The taught courses cover material related to the research interests of the academic staff. Topics covered in lectured course units normally include: set theory, group theory, dynamical systems and ergodic theory, measure theory, functional analysis, algebraic topology, Godel's theorems, hyperbolic geometry, Lie algebras, analytic number theory, Galois theory, predicate logic, computation and complexity, and other topics relevant to current mathematics.

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

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

Core courses

:

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

Optional Courses

:

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

Typical project subjects

:

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

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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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he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. Read more
he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. This discipline encompasses a wide range of life science areas, including ecology (e.g. population dynamics), epidemiology (e.g. spread of diseases), medicine (e.g. modelling cancer growth and treatment) and developmental biology.

This programme aims to equip students with the necessary technical skills to develop, analyse and interpret models applied to biological systems. Course work is supported by an extended and supervised project in life science modelling.

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

Core courses

Modelling and Tools;
Mathematical Ecology;
Dynamical Systems;
Mathematical Biology and Medicine.

Optional Courses

Optimization;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Stochastic Simulation;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Climate Change: Causes and Impacts;
Biologically Inspired Computation;
Climate Change: Mitigation and Adaptation Measures.

Typical project subjects

Population Cycles of Forest Insects;
Modelling Invasive Tumour Growth;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Wiring of Nervous System;
Vegetation Patterning in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

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The theoretical application of mathematics to the world of finance allows you to make good, informed decisions in the face of uncertainty. Read more

The theoretical application of mathematics to the world of finance allows you to make good, informed decisions in the face of uncertainty. With the growth and progression of business across the globe, the need for those who can understand quantitative financial methods are becoming increasingly lucrative, sought-after individuals. For those with a strong mathematical background, and a wish to pursue a finance career, this programme is the ideal introduction to this exciting and expanding field.To understand, apply and develop these sophisticated methods requires a good understanding of both advanced mathematics and advanced financial theory. By combining the financial expertise in the University of Exeter Business School with our internationally respected Mathematics department, this comprehensive MSc programme will prepare you for careers in areas that require expert skills in mathematical and financial modelling, computational analysis and business management.

You will gain essential, complementary skills in multiple areas of study such as probability and stochastic analysis, option pricing, risk analysis and extremes, computational methods using MATLAB/C++, financial management and investment analysis. In addition, you will branch into a specialist area of study as you conduct a substantial project in a field of your choosing. The project will allow you to develop your research, computational and modelling skills with support from staff who have extensive experience working in multiple financial services and insurance industries.

Careers

The programme prepares you for a career in financial modelling within financial institutions themselves and within other sectors. It builds upon the success of Exeter’s well-established range of Masters programmes in Finance and related areas, many of whose graduates now hold senior positions in areas such as corporate financial strategy, financial planning, treasury and risk management and international portfolio management.

With the strong links between the College and the Met Office, the course also prepares you for career opportunities within reinsurance and credit risk management, especially in the development of financial models that rely on weather/climate systems.

Programme structure

The taught element of the programme takes place between October and May and is arranged into two 12-week teaching semesters.

Compulsory modules

Recent examples of compulsory modules are as follows; Methods for Stochastics and Finance; Analysis and Computation for Finance; Mathematical Theory of Option Pricing; Fundamentals of Financial Management; Research Methodology; Advanced Mathematics Project.

Optional modules

Some recent examples are as follows; Topics in Financial Economics; Investment Analysis 1; Banking and Financial Services; Derivatives Pricing; Domestic and International Portfolio Management; Investment Analysis II; Financial Modelling; Advanced Corporate Finance; Alternative Investments; Quantitative and Research Techniques; Advanced Econometrics; Dynamical Systems and Chaos; Pattern Recognition; Introduction to C++; Level 3 Mathematics Modules.



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The MSc in Mathematics gives an in-depth training in advanced mathematics to students who have. already obtained a first degree with substantial mathematical content. Read more
The MSc in Mathematics gives an in-depth training in advanced mathematics to students who have
already obtained a first degree with substantial mathematical content. Students successfully completing the MSc will acquire specialist knowledge in their chosen areas of mathematics, and the MSc is an excellent preparation for those who are considering pursuing research in mathematics.

The main areas of mathematics that may be pursued within this MSc are pure mathematics (especially algebra and combinatorics), dynamical systems, probability and statistics, and astronomy. The MSc programme is very flexible, and in consultation with your academic adviser you may choose modules in different areas or specialise in one.

Programme outline
You will normally take eight modules in total, with one module typically comprising 24 hours of lectures and 12 hours of tutorials given during a twelve-week semester. In addition to the MSc modules offered at Queen Mary, you can also choose from an extremely wide range of advanced mathematics modules offered at other Colleges of the University of London. During the summer period, supervised by an academic member of staff, you are required to complete a dissertation, working largely independently in an advanced topic in mathematics or statistics.

For details of modules typically offered, see: http://www.maths.qmul.ac.uk/postgraduate/msc-maths-stats/modules

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Climate change is recognised as having potentially huge impacts on the environment and on human society. Read more
Climate change is recognised as having potentially huge impacts on the environment and on human society. This programme aims to provide an understanding of climate change causes, impacts, mitigation and adaptation measures from a life science perspective in conjunction with developing a wide variety of mathematical modelling skills that can be used to investigate the impacts of climate change.

The programme closely follows the structure of our Applied Mathematical Sciences MSc. Two of the mandatory courses will specifically focus on understanding the issues related to climate change and are taught by the School of Life Sciences.

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

Core courses

Modelling and Tools;
Mathematical Ecology;
Climate Change: Causes and Impacts;
Climate Change: Mitigation and Adaptation Measures;
Dynamical Systems (recommended);
Stochastic Simulation (recommended)

Optional Courses

Optimization;
Mathematical Biology and Medicine;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Applied Linear Algebra;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Bayesian Inference.

Typical project subjects

Population Cycles of Forest Insects;
Climate Change Impact;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Vegetation Patterns in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

The final part of the MSc is an extended project in mathematical modelling the impacts of climate change on environmental systems, giving the opportunity to investigate a topic in some depth guided by leading research academics.

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Quantitative financial methods are one of the fastest growing areas of the present day banking and corporate environments. Read more
Quantitative financial methods are one of the fastest growing areas of the present day banking and corporate environments. The solution by Black, Scholes and Merton of the option pricing problem set off a revolution in finance resulting in the introduction of sophisticated mathematical techniques in the financial markets and corporate planning.

To understand, apply and develop these sophisticated methods requires a good understanding of both advanced mathematics and advanced financial theory. By combining the financial expertise in the University of Exeter Business School with expertise in the Mathematical Research Institute of the Mathematics Department at the University, this intensive MSc programme, available over 9 or 12 months, will prepare you for careers in areas such as international banking or international business. For those with a strong mathematical background, and a wish to pursue a finance career, this programme is the ideal introduction to this exciting field.

Programme structure

The taught element of the programme takes place between October and May and is arranged into two 12-week teaching semesters.

Compulsory modules

The compulsory modules can include; Methods for Stochastics and Finance; Analysis and Computation for Finance; Mathematical Theory of Option Pricing; Fundamentals of Financial Management; Research Methodology and Advanced Mathematics Project;

Optional modules

Some examples of the optional modules are as follows; Topics in Financial Economics; Investment Analysis; Banking and Financial Services; Derivatives Pricing; Domestic and International Portfolio Management; Investment Analysis; Financial Modelling; Advanced Corporate Finance; Alternative Investments; Quantitative and Research Techniques; Advanced Econometrics; Dynamical Systems and Chaos; Pattern Recognition; Introduction to C++ and Level 3 Mathematics Modules.

The modules we outline here provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.

Learning and teaching

Teaching is by lectures, example classes, computer classes, tutorials, set work, project work, reading and self-study. The exact form and number of the lectures and tutorials varies from module to module and is chosen according to the material to be covered.
You will use the computer programming language Matlab and online financial databases such as Bloomberg and Datastream.

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