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.
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.
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.
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.
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)
* Introduction to Uncertainty Quantification
* Mathematical Methods
* Partial Differential Equations
* Scientific Computing
* Transferable Skills for Applied Mathematicians
OPTIONAL (3 modules, 45 credits)
* Applied Dynamical Systems (IM)
* Continuum Mechanics (IM)
* Stability theory (IM)
* Transport Phenomena and Conservation Laws (IM)
* Advanced Uncertainty Quantification (IM,NA)
* Approximation Theory and Finite Element Analysis (NA)
* Numerical Linear Algebra (NA)
* Numerical Optimization and Inverse Problems (NA)
Students registered on the Numerical Analysis pathway must select modules marked NA, and those registered on the Industrial Modelling pathway must select modules marked IM.
Syllabuses for the modules Introduction to Uncertainty Quantification and Advanced Uncertainty Quantification are currently being finalized and details will be added here as soon as possible.
Modern computing facilities are available to support the course.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
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.
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.
This programme aims to provide a rigorous formal training in computational science 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.
Options include a wide selection of modules across UCL Engineering and UCL Mathematical & Physical Sciences.
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.
Further information on modules and degree structure is available on the department website: Scientific Computing MSc
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.
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 enables 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.
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.
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 7th in QS World University Rankings 2018). Furthermore, the Thomson Scientific Citation Index shows that UCL is the second-most highly cited European university and 12th 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 enables students to tackle real-life problems in a structured and rigorous way and produce professional software for their efficient solution.
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.
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:
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.
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:
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.
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.
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 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
Advanced Fluid Mechanics
Finite Element Computational Analysis
Entrepreneurship for Engineers
Finite Element in Fluids
Nonlinear Continuum Mechanics
Computational Fluid Dynamics
Dynamics and Transient Analysis
Reservoir Modelling and Simulation
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.
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.
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.
“I gained immensely from the high quality coursework, extensive research support, confluence of cultures and unforgettable friendship.”
Prabhu Muthuganeisan, MSc Computational Mechanics
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:
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 previously offered include (both streams):
Additional compulsory courses for Computational Stream previously offered include:
Additional compulsory courses for Financial stream previously offered include:
Optional courses previously offered include:
We work closely with the Scottish Financial Risk Academy (SFRA) to offer a number of short courses led by industry (part of our Research-Linked Topics) and to provide the opportunity to our best students to write their dissertations during placements with financial services companies.
At the end of this programme you will have:
Graduates can expect to go on to work in major financial institutions or to continue their studies by joining PhD programmes.
This programme gives you a flexible syllabus to suit the demands of employers that use modern financial tools and optimization techniques in areas such as the financial sector and energy markets.
We will give you sound knowledge in financial derivative pricing, portfolio optimization and financial risk management.
We will also provide you with the skills to solve some of today’s financial problems, which have themselves been caused by modern financial instruments. This expertise includes modern probability theory, applied statistics, stochastic analysis and optimization.
Adding depth to your learning, our work placement programme puts you at the heart of financial organisations such as Moody's Analytics, Standard Life Investment and Lloyds Banking Group.
This programme involves two taught semesters of compulsory and option courses, followed by a dissertation project. You must obtain a total of 180 credits to be awarded the MSc. Over semesters 1 and 2, you will take a number of compulsory courses and optional courses. 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, possibly with one of our industry partners, for the award of the MSc degree.
We work closely with the Scottish Financial Risk Academy (SFRA) to offer a number of short courses led by industry (part of our Research-Linked Topics) and to provide the opportunity to our best students to write their dissertations during placements with financial services companies.
At the end of this programme you will have:
Graduates have gone on to work in major financial institutions or to continue their studies by joining PhD programmes.
There are no other courses that provide dedicated specialist training in design and analysis of advanced lightweight structures in aerospace, automotive, marine and renewable energy industries. This is with respect to structural integrity and health monitoring over service life, which can be tailored to your career aspirations.
Delivered with a unique focus on industry challenges and concerns, this course will equip you with strong experimental, numerical and analytical skills in structural mechanics for both composite and metallic components. This will help you to practically apply this knowledge to solve real engineering problems.
Students who enrol come from a variety of different backgrounds. Many have specific careers in mind, such as working in automotive or aerospace disciplines (structural design or crash protection), materials development for defence applications, or to work in the field of numerical code developments/consultancy.
Designing advanced structures through novel, lightweight materials is one of the key enabling technologies for both aerospace and automotive sectors to align with national targets for reduction of carbon. In reducing inherent structural weight, it is essential not to compromise safety, as structural integrity and designing for crashworthiness become key design drivers.
Understanding how aluminium or composite structures and materials perform over their life cycles under static and dynamic loading, including crash and bird strike, requires expertise in a range of areas. As new simulation and material technologies emerge, there is a continuing need for talented employees with a strong, applied understanding in structural analysis, together with competent technical skills in numerical simulation.
Established in 2003, this course is supported by close ties with industry, through student projects, specialist lectures and more importantly, by employing our graduates.
The MSc in Advanced Lightweight Structures and Impact is directed by an Industrial Advisory Panel comprising senior engineers from aerospace sectors. This maintains course relevancy and ensures that graduates are equipped with the skills and knowledge required by leading employers.
The Industry Advisory Panel includes representatives from:
The MSc in Advanced Lightweight Structures and Impact is accredited by Mechanical Engineers (IMechE) & Royal Aeronautical Society (RAes) on behalf of the Engineering Council as meeting the requirements for Further Learning for registration as a Chartered Engineer. Candidates must hold a CEng accredited BEng/BSc (Hons) undergraduate first degree to comply with full CEng registration requirements.
You will complete eight compulsory modules.
The course employs a wide range of teaching methods designed to create a demanding and varied learning environment including structured lecture programmes, tutorials, case studies, hands-on computing, individual projects, and guest lectures.
The group project aims to address one of the greatest challenges graduates face, which is the lack of experience in dealing with the complexities of working within a design team. This part of the course takes place from March to May. It is student-led and consolidates the taught material which develops both technical and project management skills on an industrially relevant project.
On successful completion of this module a student should be able to:
The projects are designed to integrate knowledge, understanding and skills from the taught modules in a real-life situation. This module is typically delivered through collaboration with an industrial sponsor.
Individual research project topics can vary greatly, allowing you to develop your own areas of interest. It is common for our industrial partners to put forward real-life practical problems or areas of development as potential research topics. This section of the course takes place from April to August.
The research projects are devised to provide a research challenge allowing you to; define the problem, perform appropriate analysis and research, draw conclusions from your work, communicate your findings and conclusions and enhance your skills and expertise. This will enable you to plan a research project, demonstrate a thorough understanding of your chosen topic area, including a critical evaluation of existing work, design appropriate analysis, plan an independent learning ability and manage a well-argued thesis report demonstrating original thought.
Cranfield University is a member of the European SOCRATES Mobility Programme and students may apply to undertake their Individual Research Project at other member institutions within Europe.
Taught modules 40%, Group project 20%, Individual research project 40%
Industry driven research makes our graduates some of the most desirable in the world for recruitment by companies competing in the structural engineering sector, which forms a large worldwide industry.
Students who enrol come from a variety of different backgrounds. Many have specific careers in mind, such as working in automotive or aerospace disciplines (structural design, or crash protection), materials development for defence applications, or to work in the field of numerical code developments/consultancy. Others decide to continue their education through PhD studies available within the University.
This course provides graduates with the necessary skills to pursue a successful career in automotive, aerospace, maritime and defence sectors. This approach offers you a wide range of career choices as a structural engineer at graduation and in the future.
Companies that have recruited graduates of this course include:
Our MSc in Applied Computational Science and Engineering will educate future domain-specialists in computational science.
This course will expand your knowledge of numerical methods, computational science, and how to solve large scale problems by applying novel science and engineering approaches. It is suitable for graduates of disciplines including maths and physical sciences, geophysics and engineering, and computer science.
This immersive, hands-on MSc course will enable students to develop their skills and techniques for a range of science and engineering applications utilising High Performance Computing resources. Students will learn alongside world-class researchers in the Department of Earth Science and Engineering.
There will be a strong emphasis on high productivity problem solving using modern computational methods and technologies, including computer code development and parallel algorithms.
Applicants who want to pursue analytical careers in industry geoscience and engineering are a target for this course. Graduates will develop the skills necessary to enter the modern industrial workforce.
This MSc will also prepare for your PhD studies in fields such as computational techniques, numerical analysis, optimisation and inversion, fluid mechanics, heat transfer, and machine learning applications.
The Applied Computational Science and Engineering MSc programme will ensure that students are able to apply appropriate computational techniques to understand, define and develop solutions to a range of science and engineering problems.
Students will have the chance to participate in individual and group research projects as well as to write reports and present technical work, developing the project management and numerical skills that employers want.
Graduates of this course will fill the market demand for those with applied, hands-on computational experience who can solve real world problems.
Through the combination of programming, foundational domain knowledge and advanced numerical literacy that this course provides, graduates will be highly sought after to work as expert analysts in industry, for example oil and gas, mineral exploration and climate science.
Graduates will be in an ideal position to pursue academic careers in fields such as computational techniques, optimisation and inversion, fluid mechanics, and machine learning applications.
For full information on this course, including how to apply, see: http://www.imperial.ac.uk/study/pg/earth-science/computational-science/
If you have any enquiries you can contact our team at: [email protected]
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