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Masters Degrees (Numerical)

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

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

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

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

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

Course content

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

Topics are drawn from four broad areas:

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

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

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

Course structure

Compulsory modules

  • Dissertation in Mathematics 60 credits

Optional modules

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

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

Learning and teaching

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

Assessment

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

Career opportunities

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

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

Careers support

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

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



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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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This one-year master's course provides training in the application of mathematics to a wide range of problems in science and technology. Read more

This one-year master's course provides training in the application of mathematics to a wide range of problems in science and technology. Emphasis is placed on the formulation of problems, on the analytical and numerical techniques for a solution and the computation of useful results.

By the end of the course students should be able to formulate a well posed problem in mathematical terms from a possibly sketchy verbal description, carry out appropriate mathematical analysis, select or develop an appropriate numerical method, write a computer program which gives sensible answers to the problem, and present and interpret these results for a possible client. Particular emphasis is placed on the need for all these parts in the problem solving process, and on the fact that they frequently interact and cannot be carried out sequentially.

The course consists of both taught courses and a dissertation. To complete the course you must complete 13 units.

There are four core courses which you must complete (one unit each), which each usually consist of 24 lectures, classes and an examination. There is one course on mathematical methods and one on numerical analysis in both Michaelmas term and Hilary term. Each course is assessed by written examination in Week 0 of the following term.

Additionally, you must choose at least least one special topic in the area of modelling and one in computation (one unit each). There are around twenty special topics to choose from, spread over all three academic terms, each usually consisting for 12 to 16 lectures and a mini project, which culminates in a written report of around 20 pages. Topics covered include mathematical biology, fluid mechanics, perturbation methods, numerical solution of differential equations and scientific programming. 

You must also undertake at least one case study in modelling and one in scientific computing (one unit each), normally consisting of four weeks of group work, an oral presentation and a report delivered in Hilary term.

There is also a dissertation (four units) of around 50 pages, which does not necessarily need to represent original ideas. Since there is another MSc focussed on mathematical finance specifically, the MSc in Mathematical and Computational Finance, you are not permitted to undertake a dissertation in this field.

You will normally accumulate four units in core courses, three units in special topics, two units in case studies and four units in the dissertation. In addition, you will usually attend classes in mathematical modelling, practical numerical analysis and additional skills during Michaelmas term.

In the first term, students should expect their weekly schedule to consist of around seven hours of core course lectures and seven hours of modelling, practical numerical analysis and additional skills classes, then a further two hours of lectures for each special topic course followed. In addition there are about three hours of problem solving classes to go through core course exercises and students should expect to spend time working through the exercises then submitting them for marking prior to the class. There are slightly fewer contact hours in the second term, but students will spend more time working in groups on the case studies.

In the third term there are some special topic courses, including one week intensive computing courses, but the expectation is that students will spend most of the third term and long vacation working on their dissertations. During this time, students should expect to work hours that are equivalent to full-time working hours, although extra hours may occasionally be needed. Students are expected to write special topic and case study reports during the Christmas and Easter vacations, as well as revising for the core course written examinations.



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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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The course provides you with a strong mathematical background with the skills necessary to apply your expertise to the solution of real finance problems. … Read more

The course provides you with a strong mathematical background with the skills necessary to apply your expertise to the solution of real finance problems. You will develop skills so that you are able to formulate a well posed problem from a description in financial language, carry out relevant mathematical analysis, develop and implement an appropriate numerical scheme and present and interpret these results.

The course lays the foundation for further research in academia or for a career as a quantitative analyst in a financial or other institution.

You will take three introductory courses in the first week. The introductory courses cover partial differential equations, probability and statistics and MATLAB.

The first term focuses on compulsory core material, offering 80 hours of lectures and 40 hours of classes/practical. The core courses are as follows:

  • Stochastic Calculus
  • Financial Derivatives
  • Numerical Methods I - Monte-Carlo
  • Numerical Methods I - Finite Differences
  • Statistics and Financial Data Analysis
  • Financial Programming with C++ 1

In the second term, three streams are offered; each stream consists of 32 hours of lectures and 16 hours of classes/practical. The Tools stream is mandatory and you will also take either the Modelling stream or the Data-driven stream.

Modelling stream

  • Exotic derivatives
  • Stochastic volatility, jump diffusions
  • Commodities
  • Fixed income

Data-driven stream

  • Asset pricing and inefficiency of markets
  • Market microstructure and trading
  • Algorithmic trading
  • Advanced financial data analysis
  • Machine learning
  • Python

Tools stream

  • Numerical methods 2 - Monte Carlo methods
  • Numerical methods 2 - Finite differences
  • Calibration
  • Optimisation
  • Introduction to stochastic control

As well as the streams, the course includes a compulsory one-week (24 hours of lectures) intensive module on quantitative risk management which is to be held in/around the week before the third term.

The third term is dedicated to a dissertation project which is to be written on a topic chosen in consultation with your supervisor.

The second component of the financial computing course, Financial Computing with C++ 2 (24 hours of lectures and practicals in total), is held shortly after the third term.

The examination will consist of the following elements:

  • two written examinations and one take-home project, each of two hours' duration - the written examinations will cover the core courses in mathematical methods and numerical analysis
  • a written examination on the Modelling stream or a written examination and a computer-based practical examination on the Data-driven stream
  • a written examination assessing the Tools stream
  • a take-home project assessing the course in quantitative risk management
  • two practical examinations assessing two courses in financial computing with C++.

Graduate destinations

MSc graduates have been recruited by prominent investment banks and hedge funds. Many past students have also progressed to PhD-level studies at leading universities in Europe and elsewhere.



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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Erasmus Mundus Computational Mechanics at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Erasmus Mundus Computational Mechanics at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

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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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. 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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