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
Students will gain deep knowledge and skills in cutting-edge computational techniques for real world science and engineering applications to meet industry demand.
The Applied Computational Science and Engineering MSc 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 mathematics and physical sciences, geophysics and engineering, and computer science.
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 are desired by employers.
The study programme consists of eight taught modules, and one individual research project which accounts for one third of the study programme.
Modern programming methods
Modelling dynamical processes
Applying computational science
Patterns for parallel programming
Inversion and optimisation
Term 3 (summer)
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, simulation, numerical modelling, optimisation and inversion, 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. You 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 desired by employers.
Duration: 1 year full-time
Start Date: October 2018
Campus: South Kensington, London
ECTS: 90 Credits
Please contact Postgraduate Education Manager, Samantha Symmonds, with any queries: [email protected]
The Applied Computational Science and Engineering MSc is subject to College approval.
The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. We are one of the UK’s largest and most prestigious academic teams in these fields.
We foster world-class interdisciplinary and collaborative research bringing together a range of disciplines.
Our research falls into three areas:
In machine learning we develop probabilistic methods that find patterns and structure in data, and apply them to scientific and technological problems. Applications include areas as diverse as astronomy, health sciences and computing.
In computational neuroscience and neuroinformatics we study how the brain processes information, and analyse and interpret data from neuroscientific experiments
The focus in the computational biology area is to develop computational strategies to store, analyse and model a variety of biological data (from protein measurements to insect behavioural data).
You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.
A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.
The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.
The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.
It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.
Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.
Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
The research you will undertake at IANC is perfectly suited to a career in academia, where you’ll be able to use your knowledge to advance this important field. Some graduates take their skills into commercial research posts, and find success in creating systems that can be used in everyday applications.
Get in at the bleeding edge of contemporary chemistry: theoretical and computational chemistry are marking the new era that lies ahead in the molecular sciences. The aim of the programme is to train scientists that are able to address a wide range of problems inmodern chemical, physical and biological sciences through the combination of theoretical and computational tools.
This programme is organised by:
The Erasmus Mundus Master of Theoretical Chemistry and Computational Modelling is a joint initiative of these European Universities, including KU Leuven and co-ordinated by the Universidad Autónoma de Madrid.
This is an initial Master's programme and can be followed on a full-time or part-time basis.
The programme is organised according to a two-year structure.
The Department of Chemistry consists of four divisions, all of which conduct highquality research embedded in well-established collaborations with other universities, research institutes and companies around the world. Its academic staff is committed to excellence in teaching and research. Although the department's primary goal is to obtain insight into the composition, structure and properties of chemical compounds and the design, synthesis and development of new (bio)molecular materials, this knowledge often leads to applications with important economic or societal benefits.
The department aims to develop and maintain leading, internationally renowned research programmes dedicated to solving fundamental and applied problems in the fields of:
Modern Chemistry is unthinkable without the achievements of Theoretical and Computational Chemistry. As a result these disciplines have become a mandatory tool for the molecular science towards the end of the 20th century, and they will undoubtedly mark the new era that lies ahead of us.
In this perspective the training and formation of the new generations of computational and theoretical chemists with a deep and broad knowledge is of paramount importance. Experts from seven European universities have decided to join forces in a European Master Course for Theoretical Chemistry and Computational Modelling (TCCM). This course is recognized as an Erasmus Mundus course by the European Union.
Graduates will have acquired the skills and competences for advanced research in chemical, physical and material sciences, will be qualified to collaborate in an international research team, and will be able to develop professional activities as experts in molecular design in pharmaceutical industry, petrochemical companies and new-materials industry.
In addition to commanding sound theoretical knowledge in chemistry and computational modelling, you will be equipped to apply any of the scientific codes mastered in the programme in a work environment, or develop new codes to address new requirements associated with research or productive activities.
You will have attained the necessary skills to pursue a scientific career as a doctoral student in chemistry, physics or material science. You will also be qualified to work as an expert in molecular design in the pharmaceutical industry, at petrochemical companies and in the new-materials industry. You will also have a suitable profile to work as a computational expert.
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 (both streams):
Optional courses - Computational stream:
Optional courses - Financial stream:
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.
The MSc in Computational Finance will introduce students to the computational methods that are widely used by practitioners and financial institutions in today's markets. This will provide students with a solid foundation not only in traditional quantitative methods and financial instruments, but also scientific computing, numerical methods, high-performance computing, distributed ledgers, big-data analytics, and agent-based modelling. These techniques will be used to understand financial markets from a post-crisis perspective which incorporates findings from the study of financial markets at high-frequency time scales, modern approaches to understanding systematic risk and financial contagion, and disruptive technologies such as distributed-ledgers and crypto-currencies. The programme is highly practical, and students will have the opportunity to apply their learning to real-world data and case studies in hands-on laboratory sessions.
Computational Finance studies problems of optimal investment, risk management and trade execution from a computational perspective. As with any engineering discipline, computational finance analyses a given problem by first building a model for it and then examining the model. In computational finance, however, our model is typically analysed by running computer programs, rather than solving mathematical equations. In addition to standard computational methods such as Monte-Carlo option pricing, you will also learn more advanced modelling techniques such as agent-based modelling, in which the model itself takes the form of a computer program.
The programme will provide a foundation in the core skills required for successful risk management and optimal investment by giving a grounding in the key quantitative methods used in finance, including computer programming, numerical methods, scientific computing, numerical optimisation, and an overview of the financial markets. You can then go on to study more advanced topics, including the market micro-structure of modern electronic exchanges, high-frequency finance, distributed-ledger technology and agent-based modelling.
Students are expected to go in to careers such as Investment Banking, Hedge Funds and Regulatory Bodies.