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The aim of this course is to enable graduates having some mathematical background attain the level required to teach the subject in schools. Read more

Overview

The aim of this course is to enable graduates having some mathematical background attain the level required to teach the subject in schools. On completion, students should attain a level of mastery comparable to that of Joint-Honours graduates in Mathematical Studies.

Students considering taking this course with a view to teaching Mathematics are strongly advised to talk to the Teaching Council in advance.

Course Structure

This is a one-year full-time course, though it may also be taken part-time over two or more years. Modules include Graph Theory, numerical Analysis, Mathematical Biology, Elementary Number theory, Introduction To Statistics, Linear Algebra, Calculus and Complex Analysis.

Career Options

The course supports students to attain the skills required to become a teacher of mathematics in secondary schools.

How To Apply

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

PAC Code
MHR57

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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The aim of this course is to enable graduates having some mathematical background attain the level required to teach the subject in schools. Read more

Overview

The aim of this course is to enable graduates having some mathematical background attain the level required to teach the subject in schools. On completion, students should attain a level of mastery comparable to that of Joint-Honours graduates in Mathematical Studies.

Students considering taking this course with a view to teaching Mathematics are strongly advised to talk to the Teaching Council in advance.

Course Structure

This is a one-year full-time course, though it may also be taken part-time over two or more years. Modules include Graph Theory, numerical Analysis, Mathematical Biology, Elementary Number theory, Introduction To Statistics, Linear Algebra, Calculus and Complex Analysis.

Career Options

The course supports students to attain the skills required to become a teacher of mathematics in secondary schools.

How To Apply

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

PAC Code

MHR56

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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Data is becoming an ever increasing part of modern life, yet the talent to extract information and value from complex data is scarce. Read more
Data is becoming an ever increasing part of modern life, yet the talent to extract information and value from complex data is scarce. This Masters will provide you with a thorough grounding in state-of-the art methods for learning from data, both in terms of statistical modelling and computation. You will also gain practical hands-on experience in carrying out various data-driven analytical projects. Previous study of Statistics or Computing Science is not required.

Why this programme?

◾The University of Glasgow’s School of Mathematics and Statistics is ranked 3rd in Scotland and 11th in the UK (Complete University Guide 2017).
◾The Statistics Group at Glasgow is the largest Statistics group in Scotland and internationally renowned for its research excellence.

Programme Structure

Core courses

◾Bayesian Statistics
◾Big Data Analytics
◾Data Management and Analytics using SAS
◾Generalised Linear Models
◾Introduction to R Programming
◾Preliminary Mathematics for Statisticians 1
◾Probability 2
◾Regression Models2
◾Statistical Inference2

One Course is optional for students with sufficient background in Linear Algebra and Calculus.

Two students who have already completed an equivalent course can substitute this course by any other optional course, including optional courses offered as part of the MRes in Advanced Statistics (see the website for details).

In your project (60 credits) you will model data collected from research in environmental science, assessed by a dissertation.

Optional courses

Students choose at least two courses from group 1 and at least one course from group 2.

Group 1
◾Artificial Intelligence
◾Information Retrieval
◾Machine Learning
◾Programming

Group 2
◾Data Analysis
◾Professional Skills

Group 3
◾Biostatistics
◾Design of Experiments
◾Environmental Statistics
◾Financial Statistics
◾Functional Data Analysis
◾Multivariate Methods
◾Spatial Statistics
◾Stochastic Processes
◾Statistical Genetics
◾Time Series

In your project (60 credits) you will tackle a complex data analytical problem or develop novel approaches to solving data analytical challenges.

Career prospects

There is a massive shortage of data-analytical skills in the workforce. Statistician is projected to be one of the fastest-growing occupations. Statistical Analysis and Data Mining was listed by LinkedIn as the hottest skill in 2014 and came second in 2015.

Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD. Our recent graduates have taken up positions as Statisticians with the Scottish Government, as Advanced Analytics Analyst at Deloitte Ireland, as Consultant at the World Bank and as Research Officer at Kenya Medical Research Institute (KEMRI).

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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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This exciting Level 6 Bachelors Degree teaches students about the latest technological developments in the IT industry, and presents them with the opportunity to pursue a career in IT or progress onto a higher award in computing at Griffith College. Read more
This exciting Level 6 Bachelors Degree teaches students about the latest technological developments in the IT industry, and presents them with the opportunity to pursue a career in IT or progress onto a higher award in computing at Griffith College.

Why Study Computing at Griffith College?

Designed specifically with the needs of industry in mind, the Higher Certificate in Computing at Griffith College is a 2-year programme, which aims to equip students with the fundamentals of computer science. Delivered on a full-time basis, as a graduate of this course, you will:

• Obtain highly sought after skills essential for a career in IT
• Obtain the necessary skills and academic requirements to further your studies with progression on to the BSc (Hons) in Computing Science at Griffith College.

Course Highlights

• Small class sizes
• Access to state of the art facilities
• A dedicated experienced lecturing team
• Industry guest speakers

Course Content

Year 1 core modules:

Business Information Systems
Computer Hardware
Computer Programming
Client Side Web Development
Effective Learning and Development
Foundations of Computing
Systems Software

Year 2 core modules:

Data Structures and Algorithms
Linear Algebra
Operating System Design
Server Side Web Development
Object Oriented Programming
Probability and Statistics
Relational Databases
Systems Analysis and Design

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

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

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

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

Why choose this course?

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

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

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

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

Department research and industry highlights

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

Course content and structure

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Assessment

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

Employability & career opportunities

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

How to apply

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

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This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications. Read more
This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications.

You will explore the mathematical techniques that are commonly used to solve problems in the real world, in particular in communication theory and in physics. As part of the course you will carry out an independent research investigation under the supervision of a member of staff. Popular dissertation topics chosen by students include projects in the areas of communication theory, mathematical physics, and financial mathematics.

The transferable skills gained on this course will open you up to a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsforapplications.aspx

Why choose this course?

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

- The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography. The academics who teach on this course include several leading researchers in these areas.

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

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

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

Department research and industry highlights

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

Course content and structure

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

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

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

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

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

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

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

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

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

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

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

On completion of the course graduates will have:
- knowledge and understanding of: the principles of communication through noisy channels using coding theory; the principles of cryptography as a tool for securing data; and the role and limitations of mathematics in the solution of problems arising in the real world

- a high level of ability in subject-specific skills, such as algebra and number theory

- developed the capacity to synthesise information from a number of sources with critical awareness

- critically analysed the strengths and weaknesses of solutions to problems in applications of mathematics

- the ability to clearly formulate problems and express technical content and conclusions in written form

- personal skills of time management, self-motivation, flexibility and adaptability.

Assessment

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

Employability & career opportunities

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

How to apply

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

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Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering. Read more

Overview

Scientific computing is a new and growing discipline in its own right. It is concerned with harnessing the power of modern computers to carry out calculations relevant to science and engineering.
By its very nature, scientific computing is a fundamentally multidisciplinary subject. The various application areas give rise to mathematical models of the phenomena being studied.

Examples range in scale from the behaviour of cells in biology, to flow and combustion processes in a jet engine, to the formation and development of galaxies. Mathematics is used to formulate and analyse numerical methods for solving the equations that come from these applications.

Implementing the methods on modern, high performance computers requires good algorithm design to produce efficient and robust computer programs. Competence in scientific computing thus requires familiarity with a range of academic disciplines. The practitioner must, of course, be familiar with the application area of interest, but it is also necessary to understand something of the mathematics and computer science involved.

Whether you are interested in fundamental science, or a technical career in business or industry, it is clear that having expertise in scientific computing would be a valuable, if not essential asset. The question is: how does one acquire such expertise?

This course is one of a suite of MScs in Scientific Computation that are genuinely multidisciplinary in nature. These courses are taught by internationally leading experts in various application areas and in the core areas of mathematics and computing science, fully reflecting the multidisciplinary nature of the subject. The courses have been carefully designed to be accessible to anyone with a good first degree in science or engineering. They are excellent preparation either for research in an area where computational techniques play a significant role, or for a career in business or industry.

Key facts:
- This course is offered in collaboration with the School of Computer Science.
- It is one of a suite of courses focusing on scientific computation.
- 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 8th in the UK in terms of research power across the three subject areas within the School of Mathematical Sciences (pure mathematics, applied mathematics, statistics and operational research).

Modules

Advanced Techniques for Differential Equations

Computational Linear Algebra

Operations Research and Modelling

Programming for Scientific Computation

Scientific Computation Dissertation

Simulation for Computer Scientists

Stochastic Financial Modelling

Variational Methods

Vocational Mathematics

Data Mining Techniques and Applications

Mathematical Foundations of Programming

English language requirements for international students

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

Further information



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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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The Master's Programme Management & Data Science is geared towards students wanting to advance their skills in the data analysis of real-world phenomena. Read more
The Master's Programme Management & Data Science is geared towards students wanting to advance their skills in the data analysis of real-world phenomena. After completion of this programme our graduates have the ability to analyze massive and complex data sets, design statistical models based on the latest in information technology. The programme is designed to meet the fast-growing demand for data scientists in business, public administration, and research.
We recommend that all those wishing to study Management & Data Science learn at least one programming language and ensure that they have a good basic grasp of linear algebra so that they are able to meet the demands of the Masters programme from the outset.

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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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This programme is for students with an undergraduate degree containing a significant component of Mathematics who wish to upgrade their degree in Mathematics and spend a year in a leading UK Mathematics Department. Read more
This programme is for students with an undergraduate degree containing a significant component of Mathematics who wish to upgrade their degree in Mathematics and spend a year in a leading UK Mathematics Department. On completion with a Merit or Distinction you may be considered for the MSc programme.

Key benefits

- An intensive programme preparing students for further study at MSc and PhD level and for work in the non-academic sector.

- A flexible programme allowing students to plan an individual programme.

- A transitional programme providing students with an excellent opportunity to upgrade their degree in Mathematics.

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/mathematics-grad-dip.aspx

Course detail

- Description -

You will attend eight of the courses currently offered to BSc or MSci students. Subject to timetable constraints, considerable choice is possible. The courses available, which change slightly from year to year, include.

- Course purpose -

For students with an undergraduate degree or equivalent who wish to have the experience of one year in a leading UK Mathematics Department, or who may not be immediately eligible for entry to a higher degree in the UK and who wish to upgrade their degree. If you successfully complete this programme with a merit or distinction we may consider you for the MSc programme.

- Course format and assessment -

You must take eight modules which may include an individual project on a subject of your choice. Examples of modules are listed below:

- Elementary Number Theory
- Partial Differential Equations & Complex Variables
- Linear Algebra
- Geometry of Surfaces
- Real Analysis II
- Complex Analysis
- Galois Theory
- Topology
- Special Relativity & Electromagnetism
- Introductory Quantum Theory
- Space-time Geometry & General Relativity
- Mathematical Finance I: Discrete Time
- Mathematical Finance II: Continuous Time
- Rings & Modules
- Representation Theory of Finite Groups
- Control Theory
- Stochastics
- Fourier Analysis
- Applied Analytic Methods
- Project (mathematical topic)

You will also take examinations, mostly in May/June.

Career prospects

Further study at MSc and PhD level, employment as analysts in investment banks and industrial researchers in large companies.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

About Postgraduate Study at King’s College London:

To study for a postgraduate degree at King’s College London is to study at the city’s most central university and at one of the top 20 universities worldwide (2015/16 QS World Rankings). Graduates will benefit from close connections with the UK’s professional, political, legal, commercial, scientific and cultural life, while the excellent reputation of our MA and MRes programmes ensures our postgraduate alumni are highly sought after by some of the world’s most prestigious employers. We provide graduates with skills that are highly valued in business, government, academia and the professions.

Scholarships & Funding:

All current PGT offer-holders and new PGT applicants are welcome to apply for the scholarships. For more information and to learn how to apply visit: http://www.kcl.ac.uk/study/pg/funding/sources

Free language tuition with the Modern Language Centre:

If you are studying for any postgraduate taught degree at King’s you can take a module from a choice of over 25 languages without any additional cost. Visit: http://www.kcl.ac.uk/mlc

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

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

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

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

Core courses

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

Optional Courses

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

Typical project subjects

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

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

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

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

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

Core courses

Modelling and Tools;
Stochastic Simulation;
Applied Linear Algebra;
Numerical Analysis;

Optional Courses

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

Typical project subjects

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

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

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

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

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

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

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

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

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

Course structure

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

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

Modules

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

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

Assessment

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

Programme aims

This programme aims to:

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

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

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

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

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

Study support

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

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

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

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

Careers

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

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

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

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