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In order to give applicants an opportunity to find out more about the MSc. programmes,. we offer 4 MSc Virtual Open Days between January and April in 2017. Read more

Virtual Open Days 2017

In order to give applicants an opportunity to find out more about the MSc
programmes,
we offer 4 MSc Virtual Open Days between January and April in 2017.

These are online sessions where you can speak to teaching staff in an informal and friendly way. It's also a great opportunity to ask any questions about the MSc.

Our next virtual open day is on:
Wednesday 19th April, 13:00 - 14:00 BST (GMT+1).

Our Virtual Open Days are live, online events so you don't have to come to the campus. There will be two presentations followed by a Question & Answer session. No preparation is required before the sessions. The presentations will cover an introduction of the MSc programmes, course contents, career opportunities, scholarships, applying and other aspects of studying with us.

Online registration is required for the events and we will accept bookings up to three days prior to each Virtual Open Day. Please go to this link to register: http://www.epcc.ed.ac.uk/msc/applying/visiting-open-days

Programme description

You will study at EPCC, the UK’s leading supercomputing centre. EPCC is the major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research.

Our staff have a wealth of expertise across all areas of HPC, parallel programming technologies and data science.

This MSc programme has a strong practical focus and provide access to leading- edge HPC systems such as ARCHER, which is the UK’s largest, fastest and most powerful supercomputer, with more than 100,000 CPU cores.

HPC is the use of powerful processors, networks and parallel supercomputers to tackle problems that are very computationally or data-intensive. You will learn leading-edge HPC technologies and skills to exploit the full potential of the world’s largest supercomputers and multicore processors. This is a well-established programme that has been successful in training generations of specialists in parallel programming.

Programme structure

The MSc programme takes the form of two semesters of taught courses followed by a dissertation project.

Your studies will have a strong practical focus and you will have access to a wide range of HPC platforms and technologies. You will take seven compulsory courses, which provide a broad-based coverage of the fundamentals of HPC, parallel computing and data science. The option courses focus on specialist areas relevant to computational science. Assessment is by a combination of coursework and examination.

Taught courses

Compulsory courses:

HPC Architectures (Semester 1)
Message-Passing Programming (Semester 1)
Programming Skills (Semester 1)
Threaded Programming (Semester 1)
Software Development (Semester 2)
Project Preparation (Semester 2)
HPC Ecosystem (Semester 2)

Optional courses:

Fundamentals of Data Management (Semester 1)
Parallel Numerical Algorithms (Semester 1)
Parallel Programming Languages (Semester 1)
Advanced Parallel Programming (Semester 2)
Data Analytics with High Performance Computing (Semester 2)
Parallel Design Patterns (Semester 2)
Performance Programming (Semester 2)
Courses from the School of Informatics, Mathematics or Physics (up to 30 credits)

Dissertation

After completing the taught courses, students work on a three-month individual project leading to a dissertation.

Dissertation projects may be either research-based or industry-based with an external organisation, with opportunities for placements in local companies.

Industry-based dissertation projects

Through our strong links with industry, we offer our students the opportunity to undertake their dissertation project with one of a wide range of local companies.

An industry-based dissertation project can give you the opportunity to enhance your skills and employability by tackling a real-world project, gaining workplace experience, exploring potential career paths and building relationships with local companies.

Career opportunities

Our graduates are employed across a range of commercial areas, for example software development, petroleum engineering, finance and HPC support. Others have gone on to PhD research in fields that use HPC technologies, including astrophysics, biology, chemistry, geosciences, informatics and materials science.

Read less
In order to give applicants an opportunity to find out more about the MSc programmes, we offer online sessions where you can speak to teaching staff in an informal and friendly way. Read more

Virtual Open Days 2017

In order to give applicants an opportunity to find out more about the MSc programmes, we offer online sessions where you can speak to teaching staff in an informal and friendly way. It's also a great opportunity to ask any questions about the MSc.

The next virtual open day is:
Wednesday 19th April, 13:00 - 14:00 BST (GMT +1)

Our Virtual Open Days are live, online events so you don't have to come to the campus. There will be two presentations followed by a Question & Answer session. No preparation is required before the sessions. The presentations will cover an introduction of the MSc programmes, course contents, career opportunities, scholarships, applying and other aspects of studying with us.

Online registration is required for the events and we will accept bookings up to three days prior to each Virtual Open Day. Please go to this link to register: http://www.epcc.ed.ac.uk/msc/applying/visiting-open-days

Programme description

You will study at EPCC, the UK’s leading supercomputing centre. EPCC is the major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research.

Our staff have a wealth of expertise across all areas of HPC, parallel programming technologies and data science.

This MSc programme has a strong practical focus and provide access to leading- edge HPC systems such as ARCHER, which is the UK’s largest, fastest and most powerful supercomputer, with more than 100,000 CPU cores.

Data science involves the manipulation, processing and analysis of data to extract knowledge, and HPC provides the power that underpins it.

You will learn the multidisciplinary skills and knowledge in both HPC and data science to unlock the knowledge contained in the increasingly large, complex and challenging data sets that are now generated across many areas of science and business.

Programme structure

This MSc programme takes the form of two semesters of taught courses followed by a dissertation project.

Your studies will have a strong practical focus and you will have access to a wide range of HPC platforms and technologies. You will take seven compulsory courses, which provide a broad-based coverage of the fundamentals of HPC, parallel computing and data science. The option courses focus on specialist areas relevant to computational science. Assessment is by a combination of coursework and examination.

Taught courses

Compulsory courses:

Fundamentals of Data Management (Semester 1)
Message-Passing Programming (Semester 1)
Programming Skills (Semester 1)
Threaded Programming (Semester 1)
Data Analytics with High Performance Computing (Semester 2)
Software Development (Semester 2)
Project Preparation (Semester 2)

Optional courses:

HPC Architectures (Semester 1)
Parallel Numerical Algorithms (Semester 1)
Parallel Programming Languages (Semester 1)
Advanced Parallel Programming (Semester 2)
HPC Ecosystem (Semester 2)
Parallel Design Patterns (Semester 2)
Performance Programming (Semester 2)
Courses from the School of Informatics, Mathematics or Physics (up to 30 credits)
Dissertation

After completing the taught courses, students work on a three-month individual project leading to a dissertation. Dissertation projects may be either research-based or industry-based with an external organisation, with opportunities for placements in local companies.

Industry-based dissertation projects
Through our strong links with industry, we offer our students the opportunity to undertake their dissertation project with one of a wide range of local companies.

An industry-based dissertation project can give you the opportunity to enhance your skills and employability by tackling a real-world project, gaining workplace experience, exploring potential career paths and building relationships with local companies.

Career opportunities

Our graduates are employed across a range of commercial areas, for example software development, petroleum engineering, finance and HPC support. Others have gone on to PhD research in fields that use HPC technologies, including astrophysics, biology, chemistry, geosciences, informatics and materials science.

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Microprocessor manufacturers have recently presented the software industry with its most serious challenge ever, by switching from serial execution architectures clocked at ever-increasing clock rates to ever-more parallel multi-core architectures clocked at a constant (or even decreasing) clock rate. Read more
Microprocessor manufacturers have recently presented the software industry with its most serious challenge ever, by switching from serial execution architectures clocked at ever-increasing clock rates to ever-more parallel multi-core architectures clocked at a constant (or even decreasing) clock rate. The consequences will be profound because parallel computational activities will need to be handled as the norm, rather than the exception; programmers of the future will need skills that are currently possessed by very few, due to the inherent complexities of parallel systems.

This pathway is centred round a core theme, Parallel Computing in the Multi-core Era , that introduces students to the aforementioned complexities, and provides techniques and tools that can alleviate the ensuing problems of correctness, reliability, performance and system management. Subsidiary themes allow students to investigate broader areas in which they might apply their newly learned skills.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Facilities

-Newly refurbished computing labs furnished with modern desktop computers
-Access to world leading academic staff
-Collaborative working labs complete with specialist computing and audio visual equipment to support group working
-Over 300 Computers in the School dedicated exclusively for the use of our students
-An Advanced Interfaces Laboratory to explore real time collaborative working
-A Nanotechnology Centre for the fabrication of new generation electronic devices
-An e-Science Centre and Access Grid facility for world wide collaboration over the internet
-Access to a range of Integrated Development Environments (IDEs)
-Specialist electronic system design and computer engineering tools

Career opportunities

Students following the Multi-Core Computing pathway have all the career options as described for general Advanced Computer Science.

In addition, students following this pathway are well placed for careers in the software industry since they will acquire the necessary skills to design and develop software that makes the most out of state-of-the-art multi-core architectures. This includes the games industry, the financial sector, and all other areas in which high performance computing is key.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with a CEng accredited Bachelors programme.

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The Marine Engineering MSc is concerned with the design, analysis and operation of machinery and systems for merchant and naval ships and submarines. Read more
The Marine Engineering MSc is concerned with the design, analysis and operation of machinery and systems for merchant and naval ships and submarines. The programme covers a wide range of engineering subjects relevant to the development and procurement of marine engineering, and the programme features two parallel mechanical and electrical streams.

Degree information

The programme comprises study in analysis and design of propulsive systems and auxiliary equipment for the latest compliant marine vessel designs as well as the use of computers in advanced engineering analysis. Students develop an understanding of elements of engineering, alongside the skills necessary to apply their knowledge in a systematic and effective manner in a group ship design exercise and an individual project.

Students undertake modules to the value of 180 credits. The programme offers two parallel streams, mechanical and electrical.

The programme consists of four core modules (60 credits), two options (30 credits) a ship design exercise (45 credits) and an independent project (45 credits).

Core modules
-Advanced Computer Applications in Engineering
-Applied Thermodynamics and Turbomachinery
-Power Transmission and Auxiliary Machinery Systems
-Vibrations, Acoustics and Control

Optional modules
Either:
-Heat Transfer and Heat Systems (Mechanical Stream)
-Materials and Fatigue (Mechanical Stream)
OR
-Electrical Machines and Power Electronic Systems (Electrical Stream)
-Electrical Power Systems & Electrical Propulsion (Electrical Stream)

Dissertation/report
All students complete a ship design exercise, working on the design of a specific vessel, and undertake an independent research project which is either analytical or design, build and test in nature.

Teaching and learning
This dynamic programme is delivered through a combination of lectures, seminars, tutorials, coursework exercises and case studies. The taught courses are assessed through formal examination and coursework, the ship design exercise is assessed through a report and oral presentations, and the individual project is assessed through a report and presentation. Visits to the marine industry are also offered.

Careers

The Marine Engineering MSc has been accredited by the Institute of Marine Engineering, Science & Technology (IMarEST) and Institute of Engineering and Technology (IET) as meeting the further learning requirements, in full, for registration as a Chartered Engineer for a period of five years, from the 2012 student cohort intake onwards.There is currently a global shortage of well-qualified marine engineers and consequently the job prospects are good.

Top career destinations for this degree:
-PhD Marine Engineering, University College London (UCL)
-Lieutenant, Koninklijke Marine (Royal Netherlands Navy)
-Marine Engineer, Ministry of Defence (MoD)
-Propulsion and Gas Turbine Systems Manager, Government of Canada
-Safety Engineer, Ministry of Defence (MoD)

Employability
Delivered by leading researchers and academics from across UCL, students will have plenty of opportunities to network and keep abreast of emerging ideas. Collaborating with companies and bodies such as the Ministry of Defence and industry leaders such as BAE Systems and Rolls Royce is key to our success and we will encourage students to develop networks through the programme itself and through the department’s careers programme, which includes employer-led events and individual coaching. We are unique in having a close relationship with the UK MoD as well Commercial Shipping companies and students benefit through industrial lectures, ship design projects and individual projects. We equip our graduates with the skills and confidence needed to play a creative and leading role in the professional and research community.

Why study this degree at UCL?

Despite being part of a central city campus university, UCL Mechanical Engineering has excellent laboratories, including engine labs and a wave tank.

This MSc has been selected by the UK Ministry of Defence (MoD), Royal Navy, Canadian and other navies for the advanced training of their marine engineers. It also receives students from many other major maritime nations. Run in parallel with the Naval Architecture MSc, students from both programmes work together on a comprehensive and unique ship design exercise.

The department has an international reputation for excellence and is funded by numerous bodies including the Royal Society, the Leverhulme Trust, UK MoD, BAE Systems, US Naval Research (ONR).

Read less
Programme structure. The programme offers four "core" modules, taken by all students, along with a variety of elective modules from which students can pick and choose. Read more
Programme structure
The programme offers four "core" modules, taken by all students, along with a variety of elective modules from which students can pick and choose. There are examinations and coursework in eight modules altogether, including the four core modules. Additionally, all students complete a dissertation.

Core modules
0.Probability and stochastics. This course provides the basics of the probabilistic ideas and mathematical language needed to fully appreciate the modern mathematical theory of finance and its applications. Topics include: measurable spaces, sigma-algebras, filtrations, probability spaces, martingales, continuous-time stochastic processes, Poisson processes, Brownian motion, stochastic integration, Ito calculus, log-normal processes, stochastic differential equations, the Ornstein-Uhlenbeck process.


0.Financial markets. This course is designed to cover basic ideas about financial markets, including market terminology and conventions. Topics include: theory of interest, present value, future value, fixed-income securities, term structure of interest rates, elements of probability theory, mean-variance portfolio theory, the Markowitz model, capital asset pricing model (CAPM), portfolio performance, risk and utility, portfolio choice theorem, risk-neutral pricing, derivatives pricing theory, Cox-Ross-Rubinstein formula for option pricing.


0.Option pricing theory. The key ideas leading to the valuation of options and other important derivatives will be introduced. Topics include: risk-free asset, risky assets, single-period binomial model, option pricing on binomial trees, dynamical equations for price processes in continuous time, Radon-Nikodym process, equivalent martingale measures, Girsanov's theorem, change of measure, martingale representation theorem, self-financing strategy, market completeness, hedge portfolios, replication strategy, option pricing, Black-Scholes formula.


0.Financial computing I. The idea of this course is to enable students to learn how the theory of pricing and hedging can be implemented numerically. Topics include: (i) The Unix/Linux environment, C/C++ programming: types, decisions, loops, functions, arrays, pointers, strings, files, dynamic memory, preprocessor; (ii) data structures: lists and trees; (iii) introduction to parallel (multi-core, shared memory) computing: open MP constructs; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.


0.Interest rate theory. An in-depth analysis of interest-rate modelling and derivative pricing will be presented. Topics include: interest rate markets, discount bonds, the short rate, forward rates, swap rates, yields, the Vasicek model, the Hull-White model, the Heath-Jarrow-Merton formalism, the market model, bond option pricing in the Vasicek model, the positive interest framework, option and swaption pricing in the Flesaker-Hughston model.

Elective modules

0.Portfolio theory. The general theory of financial portfolio based on utility theory will be introduced in this module. Topics include: utility functions, risk aversion, the St Petersburg paradox, convex dual functions, dynamic asset pricing, expectation, forecast and valuation, portfolio optimisation under budget constraints, wealth consumption, growth versus income.


0.Information in finance with application to credit risk management. An innovative and intuitive approach to asset pricing, based on the modelling of the flow of information in financial markets, will be introduced in this module. Topics include: information-based asset pricing – a new paradigm for financial risk management; modelling frameworks for cash flows and market information; applications to credit risk modelling, defaultable discount bond dynamics, the pricing and hedging of credit-risky derivatives such as credit default swaps (CDS), asset dependencies and correlation modelling, and the origin of stochastic volatility.

0.Mathematical theory of dynamic asset pricing. Financial modelling and risk management involve not only the valuation and hedging of various assets and their positions, but also the problem of asset allocation. The traditional approach of risk-neutral valuation treats the problem of valuation and hedging, but is limited when it comes to understanding asset returns and the behaviour of asset prices in the real-world 'physical' probability measure. The pricing kernel approach, however, treats these different aspects of financial modelling in a unified and coherent manner. This module introduces in detail the techniques of pricing kernel methodologies, and its applications to interest-rete modelling, foreign exchange market, and inflation-linked products. Another application concerns the modelling of financial markets where prices admit jumps. In this case, the relation between risk, risk aversion, and return is obscured in traditional approaches, but is made clear in the pricing kernel method. The module also covers the introduction to the theory of Lévy processes for jumps and its applications to dynamic asset pricing in the modern setting.

0.Financial computing II: High performance computing. In this parallel-computing module students will learn how to harness the power of a multi-core computer and Open MP to speed up a task by running it in parallel. Topics include: shared and distributed memory concepts; Message Passing and introduction to MPI constructs; communications models, applications and pitfalls; open MP within MPI; introduction to Graphics Processors; GPU computing and the CUDA programming model; CUDA within MPI; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.


0.Risk measures, preference and portfolio choice. The idea of this module is to enable students to learn a variety of statistical techniques that will be useful in various practical applications in investment banks and hedge funds. Topics include: probability and statistical models, models for return distributions, financial time series, stationary processes, estimation of AR processes, portfolio regression, least square estimation, value-at-risk, coherent risk measures, GARCH models, non-parametric regression and splines.

Research project

Towards the end of the Spring Term, students will choose a topic to work on, which will lead to the preparation of an MSc dissertation. This can be thought of as a mini research project. The project supervisor will usually be a member of the financial mathematics group. In some cases the project may be overseen by an external supervisor based at a financial institution or another academic institution.

Read less
Programme structure. The programme offers five "core" modules, taken by all candidates, along with a variety of elective modules from which students can pick and choose. Read more
Programme structure

The programme offers five "core" modules, taken by all candidates, along with a variety of elective modules from which students can pick and choose. There are lectures, examinations and coursework in eight modules altogether, including the five core modules. Additionally, all students complete an individual research project on a selected topic in financial mathematics, leading to the submission of a dissertation.

Core modules

Probability and stochastics. This course provides the basics of the probabilistic ideas and mathematical language needed to fully appreciate the modern mathematical theory of finance and its applications. Topics include: measurable spaces, sigma-algebras, filtrations, probability spaces, martingales, continuous-time stochastic processes, Poisson processes, Brownian motion, stochastic integration, Ito calculus, log-normal processes, stochastic differential equations, the Ornstein-Uhlenbeck process.

Financial markets. This course is designed to cover basic ideas about financial markets, including market terminology and conventions. Topics include: theory of interest, present value, future value, fixed-income securities, term structure of interest rates, elements of probability theory, mean-variance portfolio theory, the Markowitz model, capital asset pricing model (CAPM), portfolio performance, risk and utility, portfolio choice theorem, risk-neutral pricing, derivatives pricing theory, Cox-Ross-Rubinstein formula for option pricing.

Option pricing theory. The key ideas leading to the valuation of options and other important derivatives will be introduced. Topics include: risk-free asset, risky assets, single-period binomial model, option pricing on binomial trees, dynamical equations for price processes in continuous time, Radon-Nikodym process, equivalent martingale measures, Girsanov's theorem, change of measure, martingale representation theorem, self-financing strategy, market completeness, hedge portfolios, replication strategy, option pricing, Black-Scholes formula.


Interest rate theory. An in-depth analysis of interest-rate modelling and derivative pricing will be presented. Topics include: interest rate markets, discount bonds, the short rate, forward rates, swap rates, yields, the Vasicek model, the Hull-White model, the Heath-Jarrow-Merton formalism, the market model, bond option pricing in the Vasicek model, the positive interest framework, option and swaption pricing in the Flesaker-Hughston model.

Financial computing I. The idea of this course is to enable students to learn how the theory of pricing and hedging can be implemented numerically. Topics include: (i) The Unix/Linux environment, C/C++ programming: types, decisions, loops, functions, arrays, pointers, strings, files, dynamic memory, preprocessor; (ii) data structures: lists and trees; (iii) introduction to parallel (multi-core, shared memory) computing: open MP constructs; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.

Elective modules

Portfolio theory. The general theory of financial portfolio based on utility theory will be introduced in this module. Topics include: utility functions, risk aversion, the St Petersburg paradox, convex dual functions, dynamic asset pricing, expectation, forecast and valuation, portfolio optimisation under budget constraints, wealth consumption, growth versus income.

Information in finance with application to credit risk management. An innovative and intuitive approach to asset pricing, based on the modelling of the flow of information in financial markets, will be introduced in this module. Topics include: information-based asset pricing – a new paradigm for financial risk management; modelling frameworks for cash flows and market information; applications to credit risk modelling, defaultable discount bond dynamics, the pricing and hedging of credit-risky derivatives such as credit default swaps (CDS), asset dependencies and correlation modelling, and the origin of stochastic volatility.


Mathematical theory of dynamic asset pricing. Financial modelling and risk management involve not only the valuation and hedging of various assets and their positions, but also the problem of asset allocation. The traditional approach of risk-neutral valuation treats the problem of valuation and hedging, but is limited when it comes to understanding asset returns and the behaviour of asset prices in the real-world 'physical' probability measure. The pricing kernel approach, however, treats these different aspects of financial modelling in a unified and coherent manner. This module introduces in detail the techniques of pricing kernel methodologies, and its applications to interest-rete modelling, foreign exchange market, and inflation-linked products. Another application concerns the modelling of financial markets where prices admit jumps. In this case, the relation between risk, risk aversion, and return is obscured in traditional approaches, but is made clear in the pricing kernel method. The module also covers the introduction to the theory of Lévy processes for jumps and its applications to dynamic asset pricing in the modern setting.


Financial computing II: High performance computing. In this parallel-computing module students will learn how to harness the power of a multi-core computer and Open MP to speed up a task by running it in parallel. Topics include: shared and distributed memory concepts; Message Passing and introduction to MPI constructs; communications models, applications and pitfalls; open MP within MPI; introduction to Graphics Processors; GPU computing and the CUDA programming model; CUDA within MPI; applications to matrix arithmetic, finite difference methods, Monte Carlo option pricing.

Risk measures, preference and portfolio choice. The idea of this module is to enable students to learn a variety of statistical techniques that will be useful in various practical applications in investment banks and hedge funds. Topics include: probability and statistical models, models for return distributions, financial time series, stationary processes, estimation of AR processes, portfolio regression, least square estimation, value-at-risk, coherent risk measures, GARCH models, non-parametric regression and splines.

Research project

Towards the end of the Spring Term, students will choose a topic for an individual research project, which will lead to the preparation and submission of an MSc dissertation. The project supervisor will usually be a member of the Brunel financial mathematics group. In some cases the project may be overseen by an external supervisor based at a financial institution or another academic institution.

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

Mission and goals

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

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

Career opportunities

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

Eligible students

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

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

Presentation

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

Subjects

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

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

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

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

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

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

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

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The Centre for Doctoral Training in Pervasive Parallelism addresses the most disruptive challenge faced by the computing industry for 50 years. Read more

Research profile

The Centre for Doctoral Training in Pervasive Parallelism addresses the most disruptive challenge faced by the computing industry for 50 years. Driven by performance and energy constraints, parallelism is now crucial to all layers of the computing infrastructure, from smartphones to globally distributed systems.

This EPSRC-sponsored programme tackles the many urgent interconnected problems raised by parallel systems. How do we design programming languages for such systems? How should the architecture be structured? Which theories, tools and methodologies will allow us to reason about the behaviour of this new hardware and software?

We urgently need answers to these questions to maintain the familiar pace of technological progress, and the benefits it brings to so much of modern life. Spanning theory and practice, the centre addresses this "pervasive parallelism challenge", educating the graduates who will undertake the fundamental research and design required to transform methods and practices. As a pervasive parallelism graduate, you will develop not only deep expertise in your own specialism, but crucially, an awareness of its relationships to other facets of the challenge.

These cross-cutting synergies will enable us to unlock the true potential of current and future technologies.

This MSc is the first part of a longer 1+3 (MSc by Research + PhD) programme offered by the School through the EPSRC.

Our supervisors offer internationally leading expertise across all aspects of the pervasive parallelism challenge. These include parallel programming, wireless and mobile networking, reasoning about interaction, models of concurrent computation, energy efficient computing, systems architecture, and performance modelling.

Many more topics can be found be exploring the centre's pages and those of its supervision team and research teams. Most importantly, we believe that key research insights can be made by working across the boundaries of conventional groupings.

Training and support

We offer a four year programme, focused throughout on your development into an independent researcher, under the guidance of an expert supervision team. In the first year, you will undertake a small number of courses, and a large introductory research project, together with a range of sessions on transferable research skills.

Courses are designed to broaden your awareness of pervasive parallelism. Successful students will be awarded a Master of Research degree at this point. From this basis, the subsequent three years will be spent developing and pursuing a PhD research project, under the close supervision of your primary and secondary supervisors.

Our industrial partnerships and engagement programme will ensure that your research is informed by real world case-studies and will provide a source of diverse internship opportunities.

You will have opportunities to take up three- to six-month internships with leading companies in this area, including ARM, Intel, IBM and Microsoft, and to participate in our industrial engagement programme, exchanging ideas and challenges with our sponsor companies at brainstorming and networking events.

The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.

Facilities

You will have access to state-of-the-art facilities from on-chip accelerators including GPGPUs and multicore CPUs to the supercomputer scale systems hosted by the Edinburgh Parallel Computing Centre.

More broadly, the award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.

It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.

Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.

Among our entrepreneurial initiatives is Informatics Ventures, set up to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.

Career opportunities

We intend for our graduates to become the research leaders, both in industry and academia, whose work will lead the way into the era of mainstream parallelism. This vision is shared by our industrial supporters who have indicated their strong desire to find highly qualified candidates to fill roles in this area. We also have outstanding support for entrepreneurial initiatives through Informatics Ventures.

Our component research groups already have excellent track-records in post-graduation destinations, including the research labs of industry-leading companies, and post-doctoral research positions in top tier universities.

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This course will provide you with the opportunity to carry out an independent research project under the supervision of our leading academics. Read more
This course will provide you with the opportunity to carry out an independent research project under the supervision of our leading academics.

You will receive training in research methods and take a taught course unit in a relevant subject area. The research topic for your project is agreed with a supervisor in advance and can be in any area of the expertise in the department research groups. The project outline will be developed in consultation with your supervisor and project work is carried out in parallel with the taught courses, becoming full-time during the third term.

This Master’s by Research will provide you with a suitable background to work as a research assistant or as the grounding for further study towards a PhD.

See the website https://www.royalholloway.ac.uk/earthsciences/coursefinder/mscearthsciencesbyresearch.aspx

Why choose this course?

- This course is ideal for graduates in geology and related sciences who wish to carry out independent research over a shorter time period than is possible in a doctorate (PhD) programme. It allows you study at Master's level an aspect of the geological sciences which may not be catered for by specialist MSc programmes.

- You will be involved at every step of the research project - from planning and sample collection, laboratory work, result analysis, to writing your dissertation.

- It is ideal preparation if you are interested in studying for a PhD, but would like to have further preparation and training.

- In the 2008 Research Assessment Exercise (RAE), the Department of Earth Science’s research was ranked equal 6th in the UK with 70% rated as world-leading or internationally excellent in terms of originality, significance and rigour.

- The Department has up-to-date computer interpretation facilities, a full range of modern geochemical laboratories including XRF, quadrupole and multicollector ICP Mass Spectrometry, atmospheric chemistry and a new excimer laser ablation facility, excellent structural modelling laboratories, palaeontology and sedimentology laboratories.

Course content and structure

The course consists of the following three components:

A Research Study Skills Course Unit
- Personal research skills (e.g. safety, time and project management, teamwork)
- IT skills (e.g. literature retrieval, web authoring, databases, modelling)
- Data analysis skills (e.g. statistical methods, GIS systems, sampling techniques)
- Communication skills (e.g. posters, oral presentation, writing papers, web pages)
- Subject-specific skills and techniques. These amount to 55% of the research skills assessment, and for example may include parts of specialist taught courses (see below), a training course on the theory and practice of chemical and isotopic analysis, or other training arranged by the project supervisor. This will include training for research in the general field of the research project, not solely what is needed to carry out the project.

A Specialist Taught Course Unit
You will choose an advanced taught course unit relevant to the subject area of your research project. The following taught units are currently offered:
- Applied Sedimentology and Stratigraphy
- Pollution Sources and Pathways
- Oceans and Atmospheres
- Risk and Environmental Management
- Geographical Information Systems
- Environmental Inorganic Analysis
- Contaminants in the Environment
- Advanced Igneous Petrogenesis
- Seismic Processing and Interpretation
- Geodynamics and Plate Tectonics
- Interpretation of Structural Settings
- Coal Geology
- Petroleum Geology and Evaluation
- Terrestrial Palaeoecology
- Palaeoclimates

Research Project
The project may be on any topic which is within the broad research themes of the Department. You will be linked to a potential supervisor at the application stage and, in consultation with the supervisor, you will develop a detailed project outline during the first half of the first term. Project work is then carried out in parallel with taught courses during terms one and two, becoming the full-time activity after Easter. A bound dissertation is submitted for examination in early September.

On completion of the course graduates will have:

- an advanced knowledge and understanding of a variety of analytical, technical, numerical, modelling and interpretive techniques applicable to the specific field of earth sciences

- the articulation of knowledge and the understanding of published work, concepts and theories in the chosen field of earth sciences at an advanced level

- the acquisition of knowledge from published work in the chosen area of earth sciences to a level appropriate for a MSc degree.

Assessment

Research Study Skills: this is assessed by coursework and theory examination and will include short written assignments, a seminar, worksheets and practical tests. These assessments contribute 12.5% of the course marks.

Specialist Taught Course Units: these are mostly assessed by a written, theory examination and coursework. The unit assessment contributes 12.5% of the course marks.

Research Project: the project dissertation must be submitted in early September. It will be marked by both an internal and an external examiner, and will be defended at an oral examination with both examiners. The project assessment contributes 75% of the course marks.

Employability & career opportunities

Subject to agreement and suitable funding, MSc by Research students can transfer to the MPhil/PhD programme at Royal Holloway. They may use the research carried out for the MSc towards the PhD, and count the time spent towards MPhil/PhD registration requirements, provided that the MSc research forms a coherent part of the PhD, and that the transfer is approved prior to submission of the MSc research dissertation.

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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It is expected that applicants from the field of architecture will already possess an accredited graduate diploma or postgraduate degree in architecture (UK), a professional master's in architecture (US), or the international equivalent. Read more
It is expected that applicants from the field of architecture will already possess an accredited graduate diploma or postgraduate degree in architecture (UK), a professional master's in architecture (US), or the international equivalent.

The MArch course is an experimentally minded design studio. You will be working with students from all over the world to generate design proposals that explore the edges of architectural thought.

There is an emphasis not only on the materials and techniques of construction but also elements such as air, heat, water, sound, smell and lights as materials too. This exploration will involve visits to factories and workshops where materials are manipulated in a variety of unusual ways, and also practical experimentation and testing in the studio environment.

This programme offers the opportunity to explore ideas in great detail, resulting in a thesis that might take the form of a video, set of drawings or physical model. The portfolio generated alongside the thesis will act as a curated record of your findings.

Why choose this course?

Oxford Brookes University is unusual in offering this design-based speculative research course in architecture that builds on its excellent reputation for architectural courses at postgraduate and undergraduate level. Brookes' School of Architecture is recognised as one of the country's leading schools and is consistently ranked by The Architects' Journal as one of the five best schools in the UK.
Students from the school figure regularly in national and international prizes and awards, and go on to work for many of the best-known practices in the country. We have an international reputation in research, in areas ranging from sustainable design to modular buildings and from design for well-being to vernacular architecture.

Staff in the school regularly secure research funding from the UK's research councils and the European Union as well as industry, with an annual research grant income averaging £1,000,000 in recent years. This research expertise feeds directly into the teaching programme at all levels, from undergraduate to PhD. The School of Architecture has dedicated studio space and postgraduate facilities.

This course in detail

The Advanced Architectural Design Modules (50+30 credits) represent the core of the learning experience. Project–based learning is used in a studio environment to individually and collectively explore architectural design problems. The design studio tutors will set the specific design problem and methodology employed. It is envisaged that several parallel studios may be established, numbers permitting, each led by separate studio tutors with different agendas, programmes and methodologies. However, the learning outcomes will be common. Initially, there will be only one studio which will be organised as follows:

The first semester is always a rigid organised fabric of reviews, workshops, tutorials and deadlines with students working both individually and in groups. Within this framework students engage in two strands of investigation: A. an in-depth research into the tectonic possibilities of a new material/s and B. the analysis of a real site with the aim of generating a series of questions that demand an architectural response. By the end of the semester each student is expected to present to a jury of invited critics a catalogue both conceptual and material, from which they will make a project, in a coherent manner using appropriate media. This jury provides formative feedback for students on their learning.

The first semester design studio is complimented by a series of challenging, group and individual based workshops, Urban Cultures, on drawing, model making and movie making, run by the tutors. Students are expected to engage in questioning and debate with the lecturers and are required to produce a series of responses in drawn and written forms, which contribute to their design portfolio, around a theme related to the lecture series.

Spread over the second semester there is a further series of lectures on Architecture and the City given by external academics and practitioners. Students are expected to engage in questioning and debate with the lecturers and are required to produce a series of responses in drawn and written forms to exercises set by the visiting lecturer. The results are to be bound into a book, which contributes to and supports their design portfolio, around a theme related to the lecture series.

The second semester design studio focuses on the architectural implications of bringing the two apparently dissimilar strands of the first semester’s investigation into surprising conjunctions. Students are asked to approach the possibilities created by these apparently disconnected procedures in an entirely logical way.
At this stage the studio places emphasis on the importance of developing students’ ability to demonstrate conceptual clarity, to locate their ideas in the spectrum of current and past architecture and to maintain a strong link between concept and product.

Students are also encouraged to explore a wide range of media and technique and to develop a rationale for selecting appropriate techniques for the representation of particular kinds of architectural ideas. Students are required to present their design projects to an invited group of invited critics close to the end of the semester.

This proves formative feedback for students. The final Module mark is generated from a portfolio-based assessment held at the end of the second semester involving a panel internal staff. This system will ensure a parity of marking when the module consists of multiple design studios.

Students also undertake a Research Methods Module in the second semester that prepares them for their dissertation project. A set of generic postgraduate school-wide lectures on research paradigms, methodology and research tools is followed by Masters specific seminars in which students develop a synopsis for their dissertation’. The module is assessed by means of a review of a relevant past Masters dissertation and a synopsis proposal.

The MArch programme concludes with the Dissertation Project in which individual students work with a supervisor on projects that have developed from the work of the design studio. Students are expected to produce original, relevant and valid projects. The dissertation can take a written or design based form. In the latter case a written commentary is expected as part of the dissertation submission. Students submit their dissertation projects at the end of the summer vacation and are expected to hold an exhibition of their work in the Department or elsewhere as agreed.

Students who have qualified for the award of MA are encouraged to apply to continue to the PhD degree programme in the School if they so wish. A Postgraduate Diploma in Advanced Architectural Design can be gained by students who complete 120 credits but do not complete the full master's programme.

Teaching and learning

Studio research is complemented by a series of challenging talks by visiting academics and practitioners at every stage of the process as well as a consistent programme of individual discussions and workshops with your tutors.

You will work both in groups and individually, exploring a new kind of architecture. The methods of exploration include techniques primarily associated with the movie industry, such as the making of collages, optical composites, physical models and drawings both by hand and computer. The tutors act as guides to reveal areas of interest so that you develop an individual approach to the brief, the programme and the realisation of a project.

Teaching is heavily design-studio based, with project-based learning in a studio environment. Several parallel studies may operate, offering different methodologies but with common learning outcomes. The design studio will be complemented by a series of lectures, reviews, tutorials and site visits.

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This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet. Read more

Programme description

This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet.

You will gain a solid foundation in theoretical understanding and learn a wide variety of practical techniques that you could use in varied career settings.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

You will choose a ‘specialist area’ within the programme, which will determine the choice of your optional courses. The specialist areas are:

Analytical and Scientific Databases
Computer Systems, Software Engineering, and High Performance Computing
Programming Languages
Theoretical Computer Science

Compulsory courses:

Informatics Research Review
Informatics Research Proposal
Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
Dissertation

There are more than 50 optional courses to choose from, such as:

Machine Learning and Pattern Recognition
Probabilistic Modelling and Reasoning
Extreme Computing
Bioinformatics
Computer Graphics
Computer Networking
Human-Computer Interaction
Parallel Architectures
Parallel Programming Languages and Systems
Software Architecture, Process and Management
Algorithmic Game Theory and its Applications
Computer Algebra
Computational Complexity

Career opportunities

Through this programme you will develop specialist, advanced skills in the development, construction and management of advanced computer systems.

You will gain practical experience and a thorough theoretical understanding of the field making you attractive to a wide range of employers or preparing you for further academic study.

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This interdisciplinary Masters degree combines teaching and research from the School of Mathematics and the School of Computing. You will be introduced to sophisticated techniques at the forefront of mathematics and computer science. Read more
This interdisciplinary Masters degree combines teaching and research from the School of Mathematics and the School of Computing. You will be introduced to sophisticated techniques at the forefront of mathematics and computer science. Based on the Schools’ complementary research strengths the programme follows two main strands:

Algorithms & Complexity Theory
This concerns the efficiency of algorithms for solving computational problems, and identifies hierarchies of computational difficulty.

This subject has applications in many areas, such as distributed computing, algorithmic tools to manage transport infrastructure, health informatics, artificial intelligence, and computational biology.

Numerical Methods & Parallel Computing
Many problems, in maths, physics, astrophysics and biology cannot be solved using analytical techniques and require the application of numerical algorithms for progress. The development and optimisation of these algorithms coupled to the recent increase in computing power via the availability of massively parallel machines has led to great advances in many fields of computational mathematics. This subject has many applications, such as combustion, lubrication, atmospheric dispersion, river and harbour flows, and many more.

This MSc will provide you with technical and transferable skills that are valued by industry.

You will gain key algorithmic tools to work across many industries including transport infrastructure, health informatics, computational biology, artificial intelligence, companies developing the internet e.g. search engines.

You could also progress onto a career in computing or finance where mathematics is valued.

It will also provide you with an excellent background if you wish to embark on a PhD in mathematics or in computer science.

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The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. Read more
The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. To improve ability to solve advanced computational problems by providing a thorough knowledge of data structures, design, quantitative analysis of algorithms and algorithmic applications and impart skills necessary for algorithm implementation within the overall context of software development.

Key benefits

- Unrivalled location in the heart of London giving access to major libraries and leading scientific societies, including the BCS Chartered Institute for IT, and the Institution of Engineering and Technology (IET).

- Equips graduates with practical techniques and implementation skills for solving advanced computational problems.

- Develops critical awareness and appreciation of the changing role of computing in society, motivating graduates to pursue continuing professinoal development and further research.

- Access to speakers of international repute through seminars and external lectures, enabling students to keep abreast of emerging knowledge in advanced computing and related fields.

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/advanced-computing-msc.aspx

Course detail

- Description

This programme provides students with systematic knowledge and experience of the theoretical foundations and practice of computing at an advanced level. It is built around taught core modules such as Algorithm Design and Analysis, Data Structures and their Implementation in C++, Parallel and Distributed Algorithms, which are complemented by a wide range of optional modules for multimedia, optimisation, string processing and the web. The final part of the programme is an individual project which is closely linked with the Department's research activities.

- Course purpose

For graduates in computer science, mathematics, science or engineering with good knowledge of computer programming, this MSc will enhance your ability to solve advanced computational problems and impart skills necessary for algorithm implementation. Research for your individual project will provide valuable preparation for a career in research or industry.

- Course format and assessment

Lectures; tutorials; seminars; laboratory sessions; optional career planning workshops. Assessed through: coursework; written examinations; final project report.

- Compulsory modules:

- Algorithm Design & Analysis
- Data Structures & their Implementation in C++
- Parallel & Distributed Algorithms.

Career prospects

Via the Department’s Careers Programme, students are able to network with top employers and obtain advice on how to enhance career prospects. Our graduates have gone on to have very successful careers in general software consultancy companies, in specialised software development companies and in IT departments of large institutions (financial, telecommunications and public sector). Their jobs involve specialist programming and problem solving as well more conventional software development, maintenance and project management roles. Our graduates have also entered into academic and industrial research in software engineering, bioinformatics, algorithms and computer networks.

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

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

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

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

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

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

Course Details

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

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

Modules

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

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

Format

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

Assessment

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

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

Careers

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

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

Funding and Scholarships

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

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By combining cutting edge thinking with practical project work, MA Advertising will enable you to develop the essential skills and experience to succeed within this dynamic and challenging industry. Read more

Introduction

By combining cutting edge thinking with practical project work, MA Advertising will enable you to develop the essential skills and experience to succeed within this dynamic and challenging industry.

You'll be encouraged to develop your own creativity, produce creatively persuasive advertising work and gain an in-depth critical insight into advertising and its role in shaping society and culture.

Course content

MA Advertising combines cutting edge thinking with practical project work, enabling you to develop the intellectual abilities and gain the relevant experience needed to succeed within this dynamic and challenging industry.

This blend of academic rigor with practical experience is designed to give you in-depth critical insight into advertising and improve your understanding of the impact the media, society and culture has on individuals and organisations and in turn the role advertising plays in shaping society and culture.

MA Advertising fosters an enquiring and analytical approach to the study and practice of advertising and you’ll develop your intellectual, imaginative, creative and aesthetic skills and improve your personal professionalism and independence of judgment. You will address the nature of consumer behaviour and psychology including the role of persuasion and influence and critically assess methods for researching and measuring them. You will be encouraged to develop your own creativity and produce high quality and creatively persuasive advertising work.

You will explore your practice in ‘creative laboratory’ conditions, productive dialogue with theory and through critically supportive engagement with tutors and your peers. Your learning will be inspired and supported by an expert community of experienced academics, external specialists and practitioners from the highest levels of the industry.

Benefit from being immersed in the vibrant energy and creative community of London College of Communication; from photography exhibitions to film screenings, animation shows to interactive design installations, and masterclasses delivered by experts across the creative industries. Our emphasis on practice-based creativity and learning by doing will provide a unique and inspirational context for your own work both on the course and in your future career.

If you are interested in a career in advertising, the creative, cultural, or communication sectors, in professional research and analysis, or, more broadly, you want to become a more critical and strategic thinker, or continue your studies at doctoral level, MA Advertising is for you.

Structure

Phase One

Runs from your induction in September until January. You will take two units of study, which run in parallel: Creative Industry (40 credits) and Innovative Methods (20 credits).

Phase Two

Commences on your return in January and continues until the end of the spring term when you break for Easter. Two units running in parallel: Creative Laboratory (40 credits) and Technological Futures (20 credits).

Phase Three

Represents the culmination of your studies. Here you will engage in a self-generated research project, either through combining practice with theory or in a dissertation.

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