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This course is for you if you wish to enter knowledge-led industrial sectors or to embark upon doctoral interdisciplinary study. This interdisciplinary programme between Mathematics, Engineering, Physics, and Astronomy gives you access to a broad range of knowledge and application in industry and academia. Read more

Why is this course for you?

•This course is for you if you wish to enter knowledge-led industrial sectors or to embark upon doctoral interdisciplinary study.
•This interdisciplinary programme between Mathematics, Engineering, Physics, and Astronomy gives you access to a broad range of knowledge and application in industry and academia.

What will you gain as a student?

•practical skills in computation in a range of languages and professional software
•rigorous understanding of the theory of common numerical methods
•technical knowledge in numerical modelling
•exposure to a range of common areas of application

Core Modules

Scientific Computing
Practical Programming
Computational Methods for PDEs or Finite Element Methods

Optional Modules include:

Topics in Mathematical Biology
Particle Methods in Scientific Computing
Advanced Fluid Dynamics
Data Mining and Neural Networks
Computational Fluid Dynamics
Dynamics of Mechanical Systems
Applications in Theoretical Physics

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Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Read more
Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Numerical methods can only play an even more important role in the future as we face even bigger challenges. Therefore, skilled scientific programmers are in high demand in industry and academia and will drive forward much of the future economy.

Degree information

This programme aims to produce highly computationally skilled scientists and engineers capable of applying numerical methods and critical evaluation of their results to their field of science or engineering. It brings together best practice in computing with cutting-edge science and provides a computing edge over traditional science, engineering and mathematics programmes.

Students undertake modules to the value of 180 credits.

The programme consists of six core modules (90 credits), two optional modules (30 credits) and a dissertation/report (60 credits). A Postgraduate Diploma, six core modules (90 credits), two optional modules (30 credits), is also offered.

Core modules
-Computational and Simulation Methods
-Numerical Methods
-Numerical Optimisation
-Research Computing with C++
-Research Software Engineering with Python
-Techniques of High-Performance

Optional modules - options include a wide selection of modules across UCL Engineering and UCL Mathematical & Physical Sciences.

Dissertation/report
All students undertake an independent research project project which culminates in a dissertation of 20,000 words.

Teaching and learning
The programme is delivered through a combination of lectures and hands-on programming and includes a variety of short programming projects, delivered as part of the taught component. Students are encouraged to participate in scientific seminars, for example, weekly seminars at the UCL Centre for Inverse Problems. Assessment is through examinations, assignments, small projects and the dissertation, including a computer programme.

Careers

We expect our graduates to take up exciting science and engineering roles in industry and academia with excellent prospects for professional development and steep career advancement opportunities. This degree enable students to work on cutting-edge real-life problems, overcome the challenges they pose and so contribute to advancing knowledge and technology in our society.

Employability
Students develop a comprehensive set of skills which are in high demand both in industry and academia: professional software development skills including state-of-the-art scripting and compiled languages; knowledge of techniques used in high-performance computing; understanding and an ability to apply a wide range of numerical methods and numerical optimisation; a deeper knowledge of their chosen science subject; oral and written presentational skills.

Why study this degree at UCL?

UCL has a global reputation for excellence in research and is committed to delivering impact and innovations that enhance the lives of people in the UK, across Europe and around the world. UCL is consistently placed in the global top 20 across a wide range of university rankings (currently fifth in QS World University Rankings 2014/15). Furthermore, the Thomson Scientific Citation Index shows that UCL is the 2nd most highly cited European university and 13th in the world.

Our wide-ranging expertise provides opportunities for groundbreaking interdisciplinary investigation. World-leading experts in the field and students benefit from a programme of distinguished visitors and guest speakers in many scientific seminars. In this way a network of collaborators, mentors and peers is created, which students can access in their future career.

This degree has been designed to balance a professional software development and high performance computing skills with a comprehensive selection of numerical mathematics and scientific subjects, culminating in a scientific computing dissertation project. The dual aspect of a science and computing degree enable students to tackle real-life problems in a structured and rigorous way and produce professional software for their efficient solution.

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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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The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Read more
The MPhil programme in Scientific Computing is a full-time 12-month course which aims to provide education of the highest quality at Master’s level. Covering topics of high-performance scientific computing and advanced numerical methods and techniques, it produces graduates with rigorous research and analytical skills, who are well-equipped to proceed to doctoral research or directly into employment in industry, the professions, and the public service. It also provides training for the academic researchers and teachers of the future, encouraging the pursuit of research in computational methods for science and technology disciplines, thus being an important gateway for entering PhD programmes containing a substantial component of computational modelling.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/pcphmpscm

Course detail

The MPhil in Scientific Computing has a research and a taught element. The research element is a project on a science or technology topic which is studied by means of scientific computation. The taught element comprises of core lecture courses on topics of scientific computing and elective lecture courses relevant to the science or technology topic of the project. Most of the projects are expected to make use of the University’s High Performance Computing Service.

The students will attend lecture courses during Michaelmas Term (some courses may be during Lent Term) and then they will undertake a substantial Research Project over the next 6 months (from March to the end of August) in a participating Department. The research element aims to provide essential skills for continuation to a PhD programme or employment, as well as to assess and enhance the research capacity of the students. It is based on a science or technology topic which is studied by means of scientific computation. Research project topics will be provided by academic supervisors or by the industrial partners who are working with the participating Departments and may be sponsoring the research project.

There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively.

Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments on the core courses 25%; written examinations on the elective courses 25%.

Learning Outcomes

By the end of the course, students will have:

- a comprehensive understanding of numerical methods, and a thorough knowledge of the literature, applicable to their own research;
- demonstrated originality in the application of knowledge, together with a practical understanding of how research and enquiry are used to create and interpret knowledge in their field;
- shown abilities in the critical evaluation of current research and research techniques and methodologies;
- demonstrated self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

Format

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project.

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project. There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively. Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments 25%; written examinations 25%.

The core lectures are on topics of high performance scientific computing numerical analysis and advanced numerical methods and techniques. They are organized by the Centre for Scientific Computing and are taught and examined during the first five months (October-February). Their purpose is to provide the students with essential background knowledge for completing their dissertation and for their general education in scientific computing.

In particular, their objective is to introduce students to the simulation science pipeline of problem identification, modelling, simulation and evaluation - all from the perspective of employing high-performance computing. Numerical discretisation of mathematical models will be a priority, with a specific emphasis on understanding the trade-offs (in terms of modelling time, pre-processing time, computational time, and post-processing time) that must be made when solving realistic science and engineering problems. Understanding and working with computational methods and parallel computing will be a high priority. To help the students understand the material, the lecturers will furnish the courses with practical coursework assignments.

The lectures on topics of numerical analysis and HPC are complemented with hands-on practicals using Linux-based laptops provided by the course (students may bring their own), as well as on the University’s High Performance Computing Service.

Appropriate elective lecture courses are selected from Master’s-level courses offered by the Departments of the School of Physical Sciences, Technology or Biological Sciences. The choice of courses will be such as to provide the students with essential background knowledge for completing their theses and for their general education in the materials science application of the project. They are decided in consultation with the project supervisor. While every effort is made within the Departments to arrange the timetable in a coherent fashion, it is inevitable that some combinations of courses will be ruled out by their schedule, particularly if the choices span more than one department.

Continuing

For continuation to a PhD programme in Scientific Computing, students are required to gain a Distinction (overall grade equal or greater than 75%).

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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The development of new materials lies at the heart of many of the technological challenges we currently face, for example creating advanced materials for energy generation. Read more

Overview

The development of new materials lies at the heart of many of the technological challenges we currently face, for example creating advanced materials for energy generation. Computational modelling plays an increasingly important role in the understanding, development and optimisation of new materials. This four year Doctoral Training Programme on computational methods for material modelling aims to train scientists not only in the use of existing modelling methods but also in the underlying computational and mathematical techniques. This will allow students to develop and enhance existing methods, for instance by introducing new capabilities and functionalities, and also to create innovative new software tools for materials modelling in industrial and academic research. The first year of the CDT is a materials modelling option within the MPhil in Scientific Computing (please see the relevant entry) at the University of Cambridge and a range of additional training elements.

The MPhil in Scientific Computing is administered by the Department of Physics, but it serves the training needs of the Schools of Physical Sciences, Technology and Biological Sciences. The ability to have a single Master’s course for such a broad range of disciplines and applications is achieved by offering core (i.e. common for all students) numerical and High Performance Computing (HPC) lecture courses, and complementing them with elective courses relevant to the specific discipline applications.

In this way, it is possible to generate a bespoke training portfolio for each student without losing the benefits of a cohort training approach. This bespoke course is fully flexible in allowing each student to liaise with their academic or industrial supervisor to choose a study area of mutual interest.

See the website http://www.graduate.study.cam.ac.uk/courses/directory/pcphpdcms

Learning Outcomes

By the end of the course, students will have:
- a comprehensive understanding of numerical methods, and a thorough knowledge of the literature, applicable to their own research;
- demonstrated originality in the application of knowledge, together with a practical understanding of how research and enquiry are used to create and interpret knowledge in their field;
- shown abilities in the critical evaluation of current research and research techniques and methodologies;
- demonstrated self-direction and originality in tackling and solving problems, and acted autonomously in the planning and implementation of research.

Teaching

The first year of the CDT has a research as well as a taught element. The students attend lecture courses during the first five months (October-February) and then they will undertake a substantial Research Project over the next 6 months (from March to the end of August) in a participating Department. The research element aims to provide essential skills for a successful completion of the PhD, as well as to assess and enhance the research capacity of the students. It is based on a materials science topic which is studied by means of scientific computation. Research project topics will be provided by academic supervisors or by the industrial partners. Most of the projects are expected to make use the University’s High Performance Computing Service (for which CPU time for training and research has been budgeted for every student).

The taught element comprises core lecture courses on topics of all aspects of scientific computing, and elective lecture courses relevant to the topic of the research project. There is equal examination credit weighting between the taught and the research elements of the course, which is gained by submitting a dissertation on the project and by written assignments and examinations on the core and elective courses, respectively. Weighting of the assessed course components is as follows: Dissertation (research) 50%; written assignments 25%; written examinations 25%.

The core courses are on topics of high-performance scientific computing and advanced numerical methods and techniques; they are taught and examined during the first five months (October-February). Their purpose is to provide the students with essential background knowledge for completing their theses and for their general education in scientific computing.

Appropriate elective courses are selected from Master’s-level courses offered by the Departments of the School of Physical Sciences, Technology or Biological Sciences. The choice of courses will be such as to provide the students with essential background knowledge for completing their theses and for their general education in the materials science application of the project. They are decided in consultation with the project supervisor.

Depending on the materials science application of the research topic, students will follow one of the following two numerical methodology options: a) Continuum methods based on systems of partial differential equations (PDEs, e.g. finite-difference, element or volume methods); or b) atomistic approaches, which can be based on classical particle-based modelling (e.g. molecular dynamics) or on electronic structure- based methods (e.g. density functional theory). The students who take the atomistic modelling options will attend a 12-lecture course before continuing to classical particle-based methods or electronic structure methods. Irrespective of the numerical methodology option, students will attend lecture courses on High Performance Computing topics and elements of Numerical Analysis.

In addition to the comprehensive set of Masters-level courses provided by the MPhil and across the University in the field, which will be available to the CDT students, it will also be possible for students to take supplementary courses (not for examination) at undergraduate level, where a specific need is identified, in order to ensure that any prerequisite knowledge for the Masters courses is in place.

Moreover, depending on their background and circumstances, students may be offered places in the EPSRC-funded Autumn Academy, which takes place just before the start of the academic year (two weeks in September).

Funding Opportunities

Studentships funded by EPSRC and/or Industrial and other partners are available subject to eligibility criteria.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

Find out how to apply here http://www.graduate.study.cam.ac.uk/courses/directory/pcphpdcms/apply

See the website http://www.graduate.study.cam.ac.uk/courses/directory/pcphpdcms

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Take advantage of one of our 100 Master’s Scholarships to study Computational Mechanics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Computational Mechanics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

Swansea University has gained a significant international profile as one of the key international centres for research and training in computational mechanics and engineering. As a student on the Master's course in Erasmus Mundus Computational Mechanics, you will be provided with in-depth, multidisciplinary training in the application of the finite element method and related state-of-the-art numerical and computational techniques to the solution and simulation of highly challenging problems in engineering analysis and design.

Key Features of Erasmus Mundus Computational Mechanics MSc

The Zienkiewicz Centre for Computational Engineering is acknowledged internationally as the leading UK centre for computational engineering research. It represents an interdisciplinary group of researchers who are active in computational or applied mechanics. It is unrivalled concentration of knowledge and expertise in this field. Many numerical techniques currently in use in commercial simulation software have originated from Swansea University.

The Erasmus Mundus MSc Computational Mechanics course is a two-year postgraduate programme run by an international consortium of four leading European Universities, namely Swansea University, Universitat Politècnica de Catalunya (Spain), École Centrale de Nantes (France) and University of Stuttgart (Germany) in cooperation with the International Centre for Numerical Methods in Engineering (CIMNE, Spain).

As a student on the Erasmus Mundus MSc Computational Mechanics course, you will gain a general knowledge of the theory of computational mechanics, including the strengths and weaknesses of the approach, appreciate the worth of undertaking a computational simulation in an industrial context, and be provided with training in the development of new software for the improved simulation of current engineering problems.

In the first year of the Erasmus Mundus MSc Computational Mechanics course, you will follow an agreed common set of core modules leading to common examinations in Swansea or Barcelona. In addition, an industrial placement will take place during this year, where you will have the opportunity to be exposed to the use of computational mechanics within an industrial context. For the second year of the Erasmus Mundus MSc Computational Mechanics, you will move to one of the other Universities, depending upon your preferred specialisation, to complete a series of taught modules and the research thesis. There will be a wide choice of specialisation areas (i.e. fluids, structures, aerospace, biomedical) by incorporating modules from the four Universities. This allows you to experience postgraduate education in more than one European institution.

Modules

Modules on the Erasmus Mundus MSc Computational Mechanics course can vary each year but you could expect to study the following core modules (together with elective modules):

Numerical Methods for Partial Differential Equations
Continuum Mechanics
Advanced Fluid Mechanics
Industrial Project
Finite Element Computational Analysis
Entrepreneurship for Engineers
Finite Element in Fluids
Computational Plasticity
Fluid-Structure Interaction
Nonlinear Continuum Mechanics
Computational Fluid Dynamics
Dynamics and Transient Analysis
Reservoir Modelling and Simulation

Accreditation

The Erasmus Mundus Computational Mechanics course is accredited by the Joint Board of Moderators (JBM).

The Joint Board of Moderators (JBM) is composed of the Institution of Civil Engineers (ICE), the Institution of Structural Engineers (IStructE), the Chartered Institution of Highways and Transportation (CIHT), and the Institute of Highway Engineers (IHE).

This degree is accredited as meeting the requirements for Further Learning for a Chartered Engineer (CEng) for candidates who have already acquired an Accredited CEng (Partial) BEng(Hons) or an Accredited IEng (Full) BEng/BSc (Hons) undergraduate first degree.

See http://www.jbm.org.uk for further information.

This degree has been accredited by the JBM under licence from the UK regulator, the Engineering Council.

Accreditation is a mark of assurance that the degree meets the standards set by the Engineering Council in the UK Standard for Professional Engineering Competence (UK-SPEC). An accredited degree will provide you with some or all of the underpinning knowledge, understanding and skills for eventual registration as an Incorporated (IEng) or Chartered Engineer (CEng). Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.

Links with Industry

On the Erasmus Mundus MSc Computational Mechanics course, you will have the opportunity to apply your skills and knowledge in computational mechanics in an industrial context.

As a student on the Erasmus Mundus MSc Computational Mechanics course you will be placed in engineering industries, consultancies or research institutions that have an interest and expertise in computational mechanics. Typically, you will be trained by the relevant industry in the use of their in-house or commercial computational mechanics software.

You will also gain knowledge and expertise on the use of the particular range of commercial software used in the industry where you are placed.

Careers

The next decade will experience an explosive growth in the demand for accurate and reliable numerical simulation and optimisation of engineering systems.

Computational mechanics will become even more multidisciplinary than in the past and many technological tools will be, for instance, integrated to explore biological systems and submicron devices. This will have a major impact in our everyday lives.

Employment can be found in a broad range of engineering industries as this course provides the skills for the modelling, formulation, analysis and implementation of simulation tools for advanced engineering problems.



Student Quotes

“I gained immensely from the high quality coursework, extensive research support, confluence of cultures and unforgettable friendship.”

Prabhu Muthuganeisan, MSc Computational Mechanics

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Master’s Degree in Quantitative Finance and Risk Management draws on the recognized excellence of our engineering school in quantitative finance, and makes great use of the collaborations with the Universities of Paris-Dauphine and Cergy-Pontoise. Read more
Master’s Degree in Quantitative Finance and Risk Management draws on the recognized excellence of our engineering school in quantitative finance, and makes great use of the collaborations with the Universities of Paris-Dauphine and Cergy-Pontoise. The Master is primarily going to appeal to international students, "free movers" or those from our partner universities or for high-potential foreign engineers who are looking for an international career in the domain of finance. This program leads to a Master degree and a Diplôma accredited by the French Ministry of Higher Education and Research.

Objective

This Master’s degree covers the whole chain of quantitative finance, from theoretical aspects to the application in a professional setting. The chain can be described as follows:
o Description of the market and financial products
o Mathematical models of finance
o Mathematical models of risk
o Numerical resolution: computer-aided simulation
o Calibration and asset evaluation

Specific details of the Master:
o The Master came from the Financial Engineering option (IFI) taught at the ESITI for the last 13 years (all students from the option have found work as soon as their compulsory internships finished, and have an average salary 20% higher than the norm in this sector).
o In and of itself, the Master is intrinsically international.
o The theoretical teaching of this Master is very thorough, covering everything needed to know in the associated professions. As a consequence, the students are very adaptable within the work market.
o The Master offers a 3-skilled approach, in Computer Science, Mathematics and Finance.

Practical information
The Master’s degree counts for 120 ECTS (European Credit Transfer System) in total and lasts two years. The training lasts 1316 hours (646 hours in M1 and 670 hours in M2). The semesters are divided as follows:
o M1 courses take place from September until June and count for a total of 60 ECTS
o M2 courses take place from September until mid-April and count for a total of 44 ECTS
o A five-month internship (in France) from mid- April until mid- September for 16 ECTS. Usual indemnities are around 1000 € per month.

Non-French speakers will be asked to participate to a one week intensive French course that precedes the start of the program and allows students to gain the linguistic knowledge necessary for daily interactions.

Organization

M1 modules are taught from September to June (60 ECTS, 646 h):
• Mathematics
• Measure and Integration (2 ECTS, 20 h)
• Functional Analysis (3 ECTS, 30 h)
• Stochastic Processes-Discrete/Continuous Time (5,5 ECTS, 55 h)
• Optimization (2,5 ECTS, 30 h)
• Jump Processes and Application (3 ECTS, 30h)
• Partial Differential Equations (3 ECTS, 30 h)
 Calibration, Simulation and Numerical Analysis
• Monte Carlo Simulations (3 ECTS, 30 h)
• Finite Difference Methods (2,5 ECTS, 25 h)
• Calibration of Financial Models (2 ECTS, 20 h)
• Bloomberg trading room (3ECTS, 30h)
• C++ and Object Oriented Design (2 ECTS, 20 h)
• VBA Programming (3 ECTS, 30 h)
• Interdisciplinary Project (5 ECTS, 5 h)
 Finance and Insurance
• Introduction to Quantitative Finance (3 ECTS, 25 h)
• Risk Management in a mono-period Financial Market & Derivatives (4 ECTS, 40 h)
• Contingent Claims Valuation (3 ECTS, 30 h)
• Portfolio Management and Financial Risks (3 ECTS, 30 h)
• Mathematics Applied to Insurance (3 ECTS, 30 h)
• French as Foreign Language
• French as Foreign Language (4,5 ECTS, 96 h)

M1 modules are taught from September to June (60 ECTS, 646 h):
• Mathematics
• Measure and Integration (2 ECTS, 20 h)
• Functional Analysis (3 ECTS, 30 h)
• Stochastic Processes-Discrete/Continuous Time (5,5 ECTS, 55 h)
• Optimization (2,5 ECTS, 30 h)
• Jump Processes and Application (3 ECTS, 30h)
• Partial Differential Equations (3 ECTS, 30 h)
• Calibration, Simulation and Numerical Analysis
• Monte Carlo Simulations (3 ECTS, 30 h)
• Finite Difference Methods (2,5 ECTS, 25 h)
• Calibration of Financial Models (2 ECTS, 20 h)
• Bloomberg trading room (3ECTS, 30h)
• C++ and Object Oriented Design (2 ECTS, 20 h)
• VBA Programming (3 ECTS, 30 h)
• Interdisciplinary Project (5 ECTS, 5 h)
• Finance and Insurance
• Introduction to Quantitative Finance (3 ECTS, 25 h)
• Risk Management in a mono-period Financial Market & Derivatives (4 ECTS, 40 h)
• Contingent Claims Valuation (3 ECTS, 30 h)
• Portfolio Management and Financial Risks (3 ECTS, 30 h)
• Mathematics Applied to Insurance (3 ECTS, 30 h)
• French as Foreign Language
• French as Foreign Language (4,5 ECTS, 96 h)

M2 modules take place from September to Mid-April (60 ECTS, 670h)
• Mathematics
• Mathematical Statistics (2 ECTS, 21 h)
• Mathematical Tools in Finance (4,5 ECTS, 54h)
• Calibration, Simulation and Numerical Analysis
• Advanced Numerical Methods for PDEs in Finance(2,5 ECTS, 30 h)
• Advanced Spreadsheet Programming (2 ECTS, 24h)
• Simulations (2 ECTS, 24 h)
• Calibration (3 ECTS, 30 h)
• Theoretical and Practical Finance
• Theory of Contingent Claims (4,5 ECTS, 54 h)
• Interest Rate, Exchange and Inflation Markets (2,5 ECTS, 30 h)
• Portfolio Managment (2,5 ECTS, 30 h)
• Imperfect Markets (2 ECTS, 20 h)
• Dynamic Hedging and Risk Measures (2 ECTS, 21 h)
• Business Evaluation (2,5 ECTS, 35 h)
• Jump Processes and Applications (2 ECTS, 21 h)
• Careers and financial products (2 ECTS, 30 h)
• Practical Fixed Income Management (2 ECTS, 24 h)
• French as Foreign Language
• French as Foreign Language (4 ECTS, 72 h)
• Master's Thesis (9 ECTS, 150 h)
• Internship (22 weeks from mid-April to)

Teaching

Fourteen external teachers (lecturers from universities, teacher-researchers, professors etc.), supported by a piloting committee, will bring together the training given in Cergy.

All the classes will be taught in English, with the exception of:
• The class of FLE (French as a foreign language), where the objective is to teach the students how to understand and express themselves in French.
• Cultural Openness, where the objective is to enrich the students’ knowledge of French culture.
The EISTI offers an e-learning site to all its students, which complements everything the students will learn through their presence and participation in class:
• class documents, practical work and tutorials online
• questions and discussions between teachers and students, and among students
• a possibility of handing work in online

All Master’s students are equipped with a laptop for the duration of the program that remains the property of the EISTI.

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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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Most business schools offer an MSc in Finance. Few offer an MSc with such a strong investment component. A powerful blend of academic rigour and vocational insight, the MSc in Finance and Investment will add considerably to the knowledge of those looking to further their career in this vital sector. Read more

This programme is not currently accepting applications.

Programme description

Most business schools offer an MSc in Finance. Few offer an MSc with such a strong investment component. A powerful blend of academic rigour and vocational insight, the MSc in Finance and Investment will add considerably to the knowledge of those looking to further their career in this vital sector.

The School's location in the UK's second largest financial centre allows us to attract visiting speakers from the key financial institutions, fund management houses and a range of analysts. Students are able to interact with leading figures from many major companies; this is particularly evident in the dissertation, which offers an invaluable opportunity to collaborate on a topic that has real, of-the-minute industry relevance.

The practical, theoretical and numerical skills learnt through the programme, as well as the global perspective of investment markets and asset classes, will leave you well qualified for a range of finance related professions. We expect graduates to take up positions in investment analysis, portfolio management, financial statement analysis and evaluation, corporate finance, product development, client servicing and risk management.

The School is recognised a partner institution by the Chartered Financial Analysis (CFA) Institute. Equally the School is recognised as a Centre of Excellence in the provision of postgraduate education in finance and investment by the Chartered Institute for Securities & Investment (CISI).

Programme structure

Learning will primarily be through lectures, set reading, class discussions, exercises, group-work assignments, problem solving in tutorials and case studies. Assessment methods include examinations, assignments, presentations or continuous assessment.

Learning outcomes

Students will learn about corporate finance, global financial markets, financial accounting statements, derivatives, portfolio management, investment analysis and investment mathematics. They will also learn about the use of software and sources of information in investment and risk management.

How to estimate the fair value for an investment, to test assumptions and sensitivities and to compare different investments are explored in depth. Students will also gain an understanding of the role of different asset classes, their behaviour in isolation and in relation to other asset classes, and an understanding of how portfolios of investments can be constructed and analysed.

Intellectual skills

Students will develop:

critical analysis – an ability to assimilate new knowledge in the field of finance and investment (and to analyse the information gained) and the operations and methods used in the financial sector
research skills – an ability to identify and define pertinent research questions, to review the relevant literature, to define a proper methodology and to conduct research in the context of data analysis or other suitable methods
discipline – a major difficulty in investment is removing emotion from the decision-making process; research in behavioural finance shows that the desire of investors to follow consensus, and the ease with which they can misinterpret data, are obstacles to sound decision making - the programme will seek to imbue students with the discipline required to make good investment decisions
analytical and numerical skills – an ability to analyse and solve investment problems, to handle large volumes of numerical data, to extract and manipulate relevant data in a meaningful manner, and to analyse accounting information

Subject-specific knowledge

Students will develop:

an understanding of investment and risk-management tools and databases such as Datastream, Osiris, WRDS and ThomsonOne Banker, through use of such products and demonstrations of their output and capabilities
an understanding of industry practice in risk management and general techniques such as value-at-risk and optimisation
an ability to understand, speak and write the language of finance and investment. An ability to analyse financial statements of companies, to evaluate earnings quality and firm performance
an understanding of analytical and problem-solving methods through the use of techniques such as discounted cash flow analysis, quadratic programming, sensitivity analysis, scenario analysis and Monte Carlo Simulation
an understanding of risk and its applicability beyond investment
a knowledge of the nature and findings of academic enquiry in the areas of finance and investment

Transferable skills

Students will develop an:

ability to understand, assess and present complex lines of argument
ability to work individually and with others in teams, often under time pressure
ability to communicate clearly on paper and in presentations
enhanced numerical skills and fluency in spreadsheet use, developed through problem solving in quantitative courses within the programme

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

Programme description

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

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

This MSc programme delivers:

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

Programme structure

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

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

Compulsory courses (both streams):

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

Optional courses - Computational stream:

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

Optional courses - Financial stream:

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

Learning outcomes

At the end of this programme you will have:

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

Career opportunities

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

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Are you looking forward to a future as an expert in Agricultural, Environmental and Resource Economics? As a graduate of our Master’s Programme in Agricultural, Environmental and Resource Economics, you can find employment in the national or international market, for example at universities, research institutes, the public sector or in business, or you can become a self-employed entrepreneur. Read more
Are you looking forward to a future as an expert in Agricultural, Environmental and Resource Economics? As a graduate of our Master’s Programme in Agricultural, Environmental and Resource Economics, you can find employment in the national or international market, for example at universities, research institutes, the public sector or in business, or you can become a self-employed entrepreneur.

The Viikki Campus offers optimal resources for studying the unique range of subjects offered by our programme. Upon graduating you will be a professional in applied economics in agricultural, environmental and resource-focused fields. You will be well versed in topics such as climate policy, sustainable agriculture and food security.

The Master's programme comprises two study tracks:
1. Agricultural economics
-Languages of instruction: Finnish, Swedish, English

2. Environmental and resource economics
-Language of instruction: English

As a graduate of the study track in Agricultural Economics you will have the ability to:
-Support decision-making in the public and private sectors in various roles as a consultant, researcher or public servant.
-Analyse and communicate the impact of policies on fields relating to agriculture, the environment and natural resources.
-Apply economic theories and quantitative methodologies, such as econometrics and numerical modelling, to issues in the field.

As a graduate of the study track in Environmental and Resource economics you will have the ability to:
-Identify the socio-economic drivers of natural resource use and environmental degradation.
-Analyse the effects of policies on the environment and on natural resource usage.
-Formulate recommendations to support decision-making in both the public and private sectors.
-Apply microeconomic theory and quantitative methods (econometrics, analytical and numerical dynamic modelling, game theory).

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees: https://studyinfo.fi/wp2/en/higher-education/higher-education-institutions-will-introduce-tuition-fees-in-autumn-2017/am-i-required-to-pay-tuition-fees/

Programme Contents

Studytrack: Agricultural economics
After completing the study track in agricultural economics you will be able:
-To apply the concepts and central theories of agricultural economics.
-To apply perspectives of economic, ecological and social sustainability.
-To analyse and develop the business operations of agricultural and rural enterprises as well as intensify production in a sustainable manner.
-To analyse the operation of agricultural and food markets.
-To analyse the international political steering of agriculture.

The study track of agricultural economics combines expertise in business administration and economics with knowledge of the special features of agriculture, rural enterprises, the food market and related policies. Through studies in agricultural economics, you will learn to apply theories and models used to define the profitability and competiveness of agricultural and rural enterprises and the farm-level factors contributing to profitability and competiveness. You will examine the operation of the market and assess various policy options. The studies include practice-oriented assignments that build your decision-making and career skills, and your self-confidence to apply theoretical knowledge in practice.

Studytrack: Environmental and Resource Economics
In this studytrack you will receive a state-of-the-art economic education in environmental and natural resources policy. The courses are divided into three groups:
-Theoretically focused courses in which you will gain a deep understanding of static and dynamic models and applications of game theory.
-Courses focusing on quantitative methods in which you will gain the ability to run numerical simulations and apply econometric methods.
-Thematic courses focusing on relevant challenges in environmental and resource policy.

Selection of the Major

Studytrack: Agricultural economics
Graduates of the Bachelor’s Programme in Environmental and Food Economics can continue directly to the Master’s Programme in Agricultural, Environmental and Resource Economics, provided that they specialised in agricultural, environmental and resource economics for their Bachelor’s degree. In addition, graduates of the Bachelor’s Programme in Agricultural Sciences can continue directly to the study track in agricultural economics, provided that they have completed the module in agricultural economics for their Bachelor’s degree.

Applicants from other programmes and universities must have completed a sufficient amount of studies in economics, mathematics and statistics. Some of these studies may be incorporated into the Master’s degree as optional studies. If there are more applicants than student places, admission will be based on your previous academic performance and the applicability of your Bachelor’s degree.

Studytrack: Environmental and Resource Economics
The studytrack offers three mandatory modules and several optional modules. You can choose two thematic modules in order to focus on issues of interest to you. See the research focus below.

Programme Structure

Studytrack: Agricultural economics
The scope of the Master’s level studies is 120 credits, including both field-specific advanced studies and optional studies in the field or from other degree programmes. The minimum scope of field-specific advanced studies is 60 credits, 30 of which are accounted for by the Master’s thesis. You are recommended to focus on your Master’s thesis during your second year of Master’s studies.

The advanced studies comprise at least two modules of 15 credits. The modules are:
-Agricultural markets and policy
-Business economics
-Rural entrepreneurship
-Environmental and natural resources

In addition, your studies must include at least 15 credits of methodological studies. The studies encompass a practical training period and seminars, and they can include career orientation and career planning. You will also need to complete a personal study plan (PSP).

The scope of optional field-specific studies and studies offered by other degree programmes is 30–40 credits.

Studytrack: Environmental and Resource Economics
The studytrack lasts four semesters, lasting approximately 22 months (1st year beginning of August- 2nd year beginning of June).

Core modules (45 ECTS)
-Environmental economics
-Natural Resource Economics, dynamic optimisation and numerical models
-Environmental valuation, applied econometrics and cost-benefit analysis

Thematic modules (30 ECTS) Choose two of the following:
-Climate change
-Baltic Sea protection
-Agricultural economics and agri-environmental policy
-Forest economics

Internship and Master’s thesis seminar 15 credits (ECTS)

Master’s thesis 30 credits (ECTS)

Career Prospects

According to the labour market surveys conducted by the Finnish Association of Academic Agronomists, graduates from the study track in agricultural economics have been successful in finding employment – often before graduation. The programme alumni have found positions in various organisations in the public and private sectors in Finland, and many have pursued international careers in Europe or further afield. This study programme provides you with wide-ranging skills for starting a business and for serving in various expert or managerial positions, even if the focus of studies is on applied agriculture. Consequently, possible job titles are numerous: specialist, teacher, entrepreneur, researcher, senior officer, product manager, head of finance, etc. If you are interested in developing your expertise further, you can pursue postgraduate studies in the doctoral programmes offered by the University of Helsinki or another university in Finland or abroad.

The Environmental and Resource Economics Master of Science offers promising career paths in government, research, consultancy, industry, NGOs and international organisations.

Internationalization

-You can complete a practical training period abroad or go on a student exchange.
-You can work as a member of an international research group in Finland or abroad.
-You can complete part of your degree in English by taking courses given by international teachers.

As a student in the programme, you will have opportunities for internships, visits and study exchanges with partner universities. Visiting foreign lecturers give intensive courses as part of the thematic modules. As a student you will also be able to join our international research networks.

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This course focuses on the physical processes that generate natural hazards through an advanced understanding of geological and environmental processes. Read more

Why take this course?

This course focuses on the physical processes that generate natural hazards through an advanced understanding of geological and environmental processes.

You will be fully trained by internationally recognised experts in hazard identification, terrain evaluation techniques as well as hazard modelling and risk assessment techniques. Providing you with the essential skills to monitor, warn and help control the consequences of natural hazards.

What opportunities might it lead to?

This course is accredited by the Geological Society of London. It offers advanced professional and scientific training providing an accelerated route for you to attain Chartered Status, such as Chartered Geologist (CGeol) and Chartered Scientist (CSci) on graduation.

Here are some routes our graduates have pursued:

Aid organisations
Environmental organisations
Offshore work
Civil sector roles
Mining
Insurance companies

Module Details

You can opt to take this course in full-time or part-time mode.

The course is divided into two parts. The first part comprises the lecture, workshop, practical and field work elements of the course, followed by a five-month independent research project. The course is a mixture of taught units and research project covering topics including site investigation, hazard modelling and mapping, soil mechanics and rock mechanics, contaminated land, flooding and slope stability.

Here are the units you will study:

Natural Hazard Processes: The topic of this unit forms the backbone of the course and give you an advanced knowledge of a broad range of geological and environmental hazards, including floods, landslides, collapsible ground, volcanoes, earthquakes, tsunamis, hydro-meteorological and anthropogenic hazards. External speakers are used to provide insights and expertise from an industry, regulatory and research perspective.

Numerical Hazard Modelling and Simulation: This forms an important part of the course, whereby you are trained in the application of computer models to the simulation of a range of geological and environmental hazards. You will develop skills in computer programming languages and use them to develop numerical models that are then used to simulate different natural hazard scenarios.

Catastrophe Modelling: On this unit you will cover the application of natural hazard modelling to better understand the insurance sector exposure to a range of geological and environmental hazards. It includes external speakers and sessions on the application of models for this type of catastrophe modelling.

Volcanology and Seismology: You will gain an in-depth knowledge of the nature of volcanism and associated hazards and seismology, associated seismo-tectonics and earthquake hazards. This unit is underpinned by a residential field course in the Mediterranean region that examines the field expression of volcanic, seismic and other natural hazards.

Flooding and Hydrological Hazards: These are a significant global problem that affect urban environments, one that is likely to increase with climate change. This unit will give you an in-depth background to these hazards and opportunities to simulate flooding in order to model the flood hazard and calculate the risk.

Hazard and Risk Assessment: This unit gives you the chance to study the techniques that are employed once a hazard has been identified and its likely impact needs to be measured. You will have advanced training in the application of qualitative and quantitative approaches to hazard and risk assessment and their use in the study of different natural hazards.

Field Reconnaissance and Geomorphological Mapping: These techniques are integral to the course and an essential skill for any graduate wishing to work in this area of natural hazard assessment. On this unit you will have fieldwork training in hazard recognition using techniques such as geomorphological mapping and walk-over surveys, combined with interpretation of remote sensing and aerial photography imagery.

Spatial Analysis and Remote Sensing: You will learn how to acquire and interpret aerial photography and satellite imagery, and the integration and analysis of spatial datasets using GIS – all key tools for hazard specialists.

Geo-mechanical Behaviour of Earth Materials: You will train in geotechnical testing and description of soils and rocks to the British and international standards used by industry.

Landslides and Slope Instability: This unit will give you an advanced understanding of landslide systems, types of slides in soils and rocks and methods for identification and numerical analysis.

Impacts and Remediation of Natural Hazards: You will cover a growing area of study, including the impact of hazardous events on society and the environment, and potential mitigation and remediation methods that can be employed.

Independent Research Project: This provides you with an opportunity to undertake an original piece of research to academic or industrial standards, typically in collaboration with research staff in the department or external industry partners. In addition to submission of a thesis report, you also present the results of your project at the annual postgraduate conference held at the end of September.

Programme Assessment

The course provides a balanced structure of lectures, seminars, tutorials and workshops. You will learn through hands-on practical sessions designed to give you the skills in laboratory, computer and field techniques. The course also includes extensive field work designed to provide field mapping and data collection skills.

Assessment is varied, aimed at developing skills relevant to a range of working environments. Here’s how we assess your work:

Poster and oral presentations
Project reports
Literature reviews
Lab reports
Essays

Student Destinations

This course provides vocational skills designed to enable you to enter this specialist environmental field. These skills include field mapping, report writing, meeting deadlines, team working, presentation skills, advanced data modelling and communication.

You will be fully equipped to gain employment in the insurance industry, government agencies and specialist geoscience companies, all of which are tasked with identifying and dealing with natural hazards. Previous destinations of our graduates have included major re-insurance companies, geological and geotechnical consultancies, local government and government agencies.

It also has strong research and analytical components, ideal if you wish to pursue further research to PhD level.

We aim to provide you with as much support as possible in finding employment through close industrial contacts, careers events, recruitment fairs and individual advice.

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This course is one of the premier international applied petroleum geoscience courses. Since the inception of the course in 1985 its graduates have an unparalleled employment record in the petroleum industry both in the UK and worldwide. Read more
This course is one of the premier international applied petroleum geoscience courses. Since the inception of the course in 1985 its graduates have an unparalleled employment record in the petroleum industry both in the UK and worldwide. In addition our graduates are highly sought after for further PhD research in the petroleum geosciences.

● Recognised by NERC - 5 MSc studentships each year covering fees, fieldwork and maintenance.
● Recognised by Industry - Industry scholarships
● We offer highly focused teaching and training by internationally recognised academic experts as well as by visiting staff from the petroleum industry.

The course covers the applications of basin dynamics and evolution to hydrocarbon exploration and production. The course is modular in form providing intensive learning and training in geophysics, tectonics and structural geology, sequence stratigraphy and sedimentology, hydrocarbon systems, reservoir geology, remote sensing and applied geological fieldwork.

The MSc course provides ‘state of the art’ training in -
● 3D seismic interpretation and 3D visualization;
● Fault analysis and fault-sealing;
● Seismic sequence stratigraphy;
● Applied sedimentology;
● Well log analysis;
● Remote sensing analysis of satellite and radar imagery;
● Analysis of gravity and magnetic data;
● Numerical modelling of sedimentation and tectonics;
● Applied structural geology;
● Geological Fieldwork.

● Transferable skills learned during the course include
project planning, presentation techniques, report writing and compilation, team working skills, spreadsheet and statistical analyses, GIS methods as well as graphics and visualization techniques.

● The full time MSc course runs for 50 weeks. The first half comprises one and two week course modules as well as group projects and fieldwork. The second half of the MSc course consists of an individual research project usually carried out in conjunction with the petroleum industry or related institutions such as international geological surveys.

● Part time study over 24 months is also available


● Each year independent projects are arranged with new data sets from industry – some students work in the offices of the company whereas other may use our excellent in-house facilities. All independent projects are supervised by faculty members with additional industry supervision where appropriate.

Facilities include –
● Dedicated Modern Teaching Laboratories
● 14 Dual Screen Unix Seismic Workstations
● PC and Macintosh Workstations
● Internationally Recognised Structural Modelling Laboratories
● Advanced Sedimentological Laboratories

The MSc course also greatly benefits from dynamic interaction with internationally recognised research groups within the Geology Department including –

● Project EAGLE – Evolution of the African and Arabian rift system – Professor Cindy Ebinger
● Southeast Asia Research Group – Tectonic Evolution and Basin Development in SE Asia – Professor Robert Hall
● Numerical Modelling Research Group – Numerical Modelling of Tectonics and Sedimentation – Dr Dave Waltham
● Fault Dynamics Research Group – Dynamics of Fault Systems in Sedimentary Basins – Professor Ken McClay

The 2005 MSc graduates went on to employment with Shell, BP, Amerada Hess, Gaz de France, OMV (Austria), Star Energy, First Africa Oil, Badley Ashton, ECL, PGS, Robertsons, PGL, Aceca, and to PhD research at Royal Holloway and Barcelona.
Since 2001, 85% of our graduates have gone in to work in the oil industry, 10% into geological research and 5% into environmental/engineering jobs.

Accommodation is available on campus in en-suite study bedrooms grouped in flats of eight, each with a communal kitchen and dining space.

Subsistence Costs ~£9,000 pa (including Hall of Residence fees of c. £4,500 for a full year)

APPLICATIONS can be made on line at http://www.rhul.ac.uk/Registry/Admissions/applyonline.html

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This is one of the premier international applied MSc courses with a focus on petroleum exploration and production. It is run in parallel with the Basin Evolution and Dynamics MSc in Petroleum Geocsience but with a greater emphasis on tectonics and structural geology. Read more
This is one of the premier international applied MSc courses with a focus on petroleum exploration and production. It is run in parallel with the Basin Evolution and Dynamics MSc in Petroleum Geocsience but with a greater emphasis on tectonics and structural geology. In addition to successful employment in the international petroleum industry graduates from this course are employed in the international mining industry as well as being highly sought after for further PhD research in the geosciences.

● Recognised by Industry - Industry scholarships

● We offer highly focused teaching and training by internationally recognised academic experts as well as by visiting staff from the petroleum and remote sensing industries.

The course covers the applications of tectonics and structural geology to hydrocarbon exploration and production as well as to applied structural geology research in different terranes. The course is modular in form providing intensive learning and training in tectonics, applied structural geology, seismic interpretation of structural styles, tectonostratigraphic analysis, section balancing and reconstruction, remote sensing, crustal fluids and hydrocarbon systems, reservoir geology, and applied geological fieldwork.

The MSc course provides ‘state of the art’ training in –
● Plate tectonics and terrane analysis;
● Applied structural analysis;
● 3D seismic interpretation and 3D visualization of structural styles;
● Fault analysis and fault-sealing;
● Tectonostratigraphic analysis;
● Scaled analogue modelling;
● Numerical modelling of structures;
● Remote sensing analysis of satellite and radar imagery;
● Analysis of gravity and magnetic data;
● Section balancing and reconstruction;
● Applied structural fieldwork.

● Transferable skills learned during the course include
project planning, presentation techniques, report writing and compilation, team working skills, spreadsheet and statistical analyses, GIS methods as well as graphics and visualization techniques.

● The full time MSc course runs for 50 weeks. The first half comprises one and two week course modules as well as group projects and fieldwork. The second half of the MSc course consists of an individual research project usually carried out in conjunction with the petroleum industry or related institutions such as international geological surveys.

● Part time study over 24 months is also available

● Each year independent projects are arranged with new data sets from industry – some students work in the offices of the company whereas other may use our excellent in-house facilities. All independent projects are supervised by faculty members with additional industry supervision where appropriate.

Facilities include –
● Dedicated Modern Teaching Laboratories
● Internationally Recognised Structural Modelling Laboratories
● 14 Dual Screen Unix Seismic Workstations
● PC and Macintosh Workstations
● Advanced Sedimentological Laboratories

The MSc course also greatly benefits from dynamic interaction with internationally recognised research groups within the Geology Department including –

● Project EAGLE – Evolution of the African and Arabian rift system – Professor Cindy Ebinger
● Southeast Asia Research Group – tectonic evolution and basin development in SE Asia – Professor Robert Hall
● Numerical Modelling Research Group – Numerical modelling of tectonics and sedimentation – Dr Dave Waltham
● Fault Dynamics Research Group – Dynamics of Fault Systems in Sedimentary Basins – Professor Ken McClay

Our Tectonics MSc graduates have gained employment with Shell, BP, ECL, PGS, Sipetrol, PGL, Codelco, and to PhD research in a range of universities including Trieste, Barcelona, and Ulster universities.
Since 2001, 85% of our Petroleum Geosciences MSc graduates have gone in to work in the oil industry, 10% into geological research and 5% into environmental/engineering jobs.

Accommodation is available on campus in en-suite study bedrooms grouped in flats of eight, each with a communal kitchen and dining space.

Subsistence Costs ~£9,000 pa (including Hall of Residence fees of c. £4,500 for a full year)

APPLICATIONS can be made on line at http://www.rhul.ac.uk/Registry/Admissions/applyonline.html

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This programme is a comprehensive and intensive investigation into key areas in accounting and finance. Designed for those with a quantitative background, it is both academically rigorous and closely in line with professional practice. Read more

Programme description

This programme is a comprehensive and intensive investigation into key areas in accounting and finance. Designed for those with a quantitative background, it is both academically rigorous and closely in line with professional practice.

The MSc in Accounting and Finance is especially useful for those graduates with work experience in accounting looking to gain essential practical skills in finance - and, of course, vice versa. Although the compulsory core courses ensure a good balance between both accounting and finance study, the option courses give students the opportunity to specialise - tailoring their studies towards their chosen career.

Studying accounting and finance in Edinburgh gives students the opportunity to base themselves at the heart of the UK's second largest financial centre.

Many of Europe's leading financial institutions have their headquarters here, a fact that we make full use of on the MSc programme. We regularly bring guest speakers to the School to talk directly to accounting and finance students on real, current practice. The School also maintains good relationships with a number of accounting and finance professionals who will be on hand to provide advice on research and career opportunities. It is essential connections like these that characterise the dynamic nature of this strongly vocational programme.

Our strong connection to industry is exemplified by our work in the Centre for Financial Markets Research, and the Institute of Public Sector Accounting Research. Bringing together leading academics and practitioners, the centres are a keen theatre of debate, creating new thoughts, new ideas for both the theoretical study and practical application of accounting, finance and investment.

Programme structure

Learning will primarily be through lectures, set reading, class discussions, exercises, group-work assignments, problem solving in tutorials and case studies. Assessment methods include examinations, assignments, presentations or continuous assessment.

Learning outcomes

This programme enables students to analyse financial statements and to show the links between accounting statements, valuation methods and investment analysis.

Knowledge and understanding

Students will gain knowledge of global financial markets and the finance and investment industry – how different organisations interact, their roles, and factors behind success or failure. Students will learn how to estimate the fair value for an investment, to test assumptions and sensitivities, and to compare different investments.

Students will gain an understanding of the role of different asset classes, their behaviour in isolation and in relation to other asset classes, and an understanding of how portfolios of investments can be constructed and analysed.

Intellectual skills

Students will develop:

Critical analysis skills – an ability to assimilate new knowledge in the field of accounting and finance as well as the capacity to provide critical analysis of the field.
Research skills – an ability to identify and define pertinent research questions, to review the relevant literature, to define a proper methodology and to conduct research in the context of data analysis or experiments.
Discipline - a major difficulty in investment is removing emotion from the decision-making process. Study into behavioural finance shows that the desire of investors to follow consensus, and the ease with which they can misinterpret data, are obstacles to sound decision making. The programme will seek to imbue students with the discipline required to make good investment decisions.
Analytical and numerical skills - an ability to analyse and solve valuation and investment problems, to handle large volumes of numerical data and extract and manipulate relevant data in a meaningful manner.

Professional/subject-specific/practical skills

Students will develop:

An understanding of accounting, investment and risk management tools and databases such as Datastream, Reuters 3000Xtra, ThomsonOne Banker, CRSP, COMPUSTAT, London Share Price Database and WRDS.
An ability to: analyse and interpret financial data (such as financial statements); and to evaluate earnings quality and firm performance through individual and collaborative projects.
An understanding of analytical and problem-solving methods through the use of techniques such as discounted cash flow analysis.

Transferable skills

These include enhanced numerical skills and fluency in spreadsheet use and the ability to communicate challenging material both orally and in writing.

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