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Masters Degrees (Computational)

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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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Study a degree which develops your arts practice through the expressive world of creative computation. The Masters provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition. Read more

Study a degree which develops your arts practice through the expressive world of creative computation. The Masters provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition.

What is computational art?

Computation consists of all the changes brought about by digital technology. Art is an open set of ways of acting inventively in culture. Mixing the two together in a systematic way gives us computational art. This is a very open field, and one that is set to expand enormously in the coming years. It is where the most exciting developments in technology and in culture can already be found. This degree will place you in the middle of this fast-evolving context.

What will I learn?

This degree develops your arts practice through the expressive world of creative computation. Over a two years (full-time) or four years (part-time) you will develop your artistic work and thinking through the challenge of developing a series of projects for public exhibition which will explore the technological and cultural ramifications of computation. 

You will learn the fundamentals of programming and how to apply this knowledge expressively. You will work with popular open source programming environments such as Processing, OpenFrameworks, P5.js and Arduino, and will learn how to program in languages such as Java, Javascript and C++. 

Since computational artworks don’t necessarily involve computers and screens, we also encourage students to produce works across a diverse range of media. Supported by studio technicians in state-of-the-art facilities, our students are producing works using tools such as 3D printers, laser cutters, robotics, wearable technologies, paint, sculpture and textiles. 

You will also study contextual modules on computational art and the socio-political effects of technology. Modules provide students with the historical foundations, frameworks, critical skills and confidence to express their ideas effectively. You will have the opportunity to learn the cultural histories of technology, to reflect on computation in terms of its wider cultural effects, and to understand the way in which art provides rigorous ways of thinking. 

Through our masterclass series, we regularly invite world-class artists and curators to explain their work and engage in critical dialogue with the students. This allows you to develop a wider understanding of the contemporary art scene and how your work sits within the professional art world.

Should I study the MFA or MA Computational Arts?

As well as the MFA, we also offer an MA in Computational Arts. The MA is 1 year (full-time), the MFA 2 years (full-time).

The first year of the MFA is identical to the MA. You take the same classes and you learn the same things. The differences between the two courses is that in the MFA you get a 2nd year in which you take additional courses which help you develop your arts practice further. These courses mean that you get a space to work under a tutor's supervision.

Modules & structure

Year 1

Year 1 shares the same core learning as our MA in Computational Arts programme: 

The follwing are core modules:

You may then pick modules of your own choice from the optional modules listed below: 

In year 2 you will study the following: 

Assessment  

In Year 2 you will be assessed by: self-evaluation report of 2,500 words; essay of up to 6,000 words; viva voce; exhibition of final work.

Skills & careers

The programme will equip you with a broad training in the use of creative computing systems that are currently most important in artistic, design and cultural practices and the creative industries, as well as technologies that are yet to emerge.

Find out more about employability at Goldsmiths



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Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges the scientific community is currently working on. Read more

Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges the scientific community is currently working on. Computational cognitive neuroscience is a young and exciting discipline that tackles these long-standing research questions by integrating computer modelling with experimental research.

This Masters programme will foster a new generation of scientists who will be trained in both neuro-computational modelling as well as cognitive neuroscience. Its core topics include:

  • Creating computational/mathematical models of neurons, circuits and cognitive functions
  • The fundamentals of cognitive neuroscience (brain mechanisms and structures underlying cognition and behaviour)
  • Advanced data analysis and neuroimaging techniques

The programme is suitable for students from a variety of disciplines including - but not limited to - psychology, computing, neuroscience, engineering, biology, maths and physics. Students with no prior programming experience are welcome.

Graduates of this Masters will acquire a unique set of complementary skills that will make them extremely competitive in securing research or analyst positions in both academia and industry.

Why study this course?

  • This cutting-edge programme is at the forefront of a new, rapidly emerging field of research.
  • It is multidisciplinary, conveying the theory and practice of computational and cognitive neurosciences.
  • Graduates of this programme will gain a competitive edge in the job market over graduates of other, standard programmes in related fields.

Modules & structure

You will study the following core modules:

You will also undertake a 60 credit research project investigating an aspect of cognitive neuroscience using computational modelling, advanced data analysis methods, or a combination of these techniques. Culminating in a 10,000 word dissertation, the project will be carried out by combining the computational, experimental and data analysis skills that students will acquire over Term 1 and 2.

Option modules

You will choose one option from the following two modules:

  • Data Programming
  • Introduction to MATLAB

You will also choose one of the following 4 options:

Please note that due to staff research commitments not all of these modules may be available every year.

Skills & careers

Graduates of this programme will have the following assets in their portfolio:

  • A sound understanding of brain mechanisms and structures underlying cognition and behaviour
  • Knowledge or experience of experimental cognitive neuroscience methods
  • Skills in statistical data analysis
  • Knowledge of theory and practice of biologically constrained neural models of human brain function
  • Computer programming skills.

Such a cross-disciplinary profile will make graduates of this Masters particularly competitive on the job market, especially when applying for positions that require complementary expertise and skills.

The course prepares students for employment in areas including cognitive neuroscience, IT consultancy, cognitive robotics, as well as large enterprises developing software systems inspired by human cognition (e.g., web-search engines, systems for natural language processing, information extraction, data mining and human-computer interaction).

The course is also ideal preparation for further study at PhD level.



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Inspiring the future crop of experts in Computational Science and Engineering. Students will gain deep knowledge and skills in cutting-edge computational techniques for real world science and engineering applications to meet industry demand. Read more

Inspiring the future crop of experts in Computational Science and Engineering

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.

  • Preparing tomorrow’s technologists, entrepreneurs and computational problem solvers
  • Large scale, big data, machine learning
  • Model dynamical processes using numerical methods and advanced programming
  • Combining mathematics, physical sciences, engineering, and computational science

Study Programme

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.

Term 1

Modern programming methods

Modelling dynamical processes

Numerical methods

Applying computational science

Term 2

Advanced programming

Patterns for parallel programming

Inversion and optimisation

Machine learning

Term 3 (summer)

Independent Project

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.

Key Information

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: 

Flyer for new Applied Computational Science and Engineering MSc

The Applied Computational Science and Engineering MSc is subject to College approval.

Find out more about postgraduate study at Imperial College London, including tuition fees, admissions and how to apply.



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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. Read more

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:

  • machine learning
  • computational neuroscience
  • computational biology

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).

Training and support

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.

Facilities

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.

Career opportunities

The research you will undertake at ANC 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.



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This new and unique course covers a wide range of applications focused on aerospace computational aspects. As mirrored by developments in the motorsport industry, within the next five years there will be a demand for engineers and leaders who will be using 100% digital techniques for aeronautical design and testing. Read more

This new and unique course covers a wide range of applications focused on aerospace computational aspects. As mirrored by developments in the motorsport industry, within the next five years there will be a demand for engineers and leaders who will be using 100% digital techniques for aeronautical design and testing.

Who is it for?

With its blend of skills-based and subject-specific material this course aims to provide students with generic practical skills and cutting-edge knowledge adaptable to the wide variety of applications in the field of aerospace computational engineering.

The part-time option is suitable for qualified engineers to extend their knowledge and incorporate CFD into their skill set.

Why this course?

This course aims to enhance your skills through a detailed introduction to the state-of-the-art computational methods and their applications for digital age aerospace engineering applications. It provides a unique opportunity for cross-disciplinary education and knowledge transfer in the computational engineering of fluid and solid mechanics for aerospace industrial applications. Focusing on fully integrated digital design for aerospace applications you will be able to understand and implement numerical methods on various computing platforms for aerospace applications. You will be able to meet the demand of an evolving workplace that requires highly qualified engineers possessing core software engineering skills together with competency in mathematical analysis techniques.

Sharing modules with the MSc in Computational Fluid Dynamics and the MSc in Computational and Software Techniques in Engineering this course gives you the opportunity to interact with students from other disciplines.

Informed by Industry

Our strategic links with industry ensures that all of the materials taught on the course are relevant, timely and meet the needs of organisations competing within the computational analysis sector. This industry led education makes Cranfield graduates some of the most desirable for companies to recruit. Our industrial partners support this course by providing internship, act as visiting lectures and deliver industrial seminars.

Accreditation

Following the first graduation, this course will seek to obtain accreditation from:

Course details

The taught modules are delivered from October to April via a combination of structured lectures, and computer based labs. Many of the lectures are given in conjunction with some form of programming, you will be given time and practical assistance to develop your software skills.

Students on the part-time programme complete all of the compulsory modules based on a flexible schedule that will be agreed with the course director.

Group project

The Group project is related to digital wind tunnel development.

Individual project

The taught element of the course finishes in May. From May to September you will work full-time on your individual research project. The research project gives you the opportunity to produce a detailed piece of work either in close collaboration with industry, or on a particular topic which you are passionate about.

Assessment

Taught modules: 80%, Group project: 40%, Individual Research Project: 80%

Your career

The MSc in Aerospace Computational Engineering is designed to equip you with the skills required to pursue a successful career working in the UK and overseas in computational aeronautic design and engineering. 

Our courses attract enquiries from companies in the rapidly expanding engineering IT industry sector across the world who wish to recruit high quality graduates who have strong technical programming skills in industry standard languages and tools. They are in demand by CAD vendors, commercial engineering software developers, aerospace, automotive and other industries and research organisations, and have been particularly successful in finding employment.

Some of our graduates go onto PhD degrees. Project topics are most often supplied by individual companies on in-company problems with a view to employment after graduation – an approach that is being actively encouraged by a growing number of industries.



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What is the Erasmus Mundus Master of Science in Theoretical Chemistry and Computational Modelling all about?. Get in at the bleeding edge of contemporary chemistry. Read more

What is the Erasmus Mundus Master of Science in Theoretical Chemistry and Computational Modelling all about?

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:

  • Universidad Autónoma de Madrid (coordinating institution), Spain
  • Universiteit Groningen, the Netherlands
  • KU Leuven, Belgium
  • Università degli Studi di Perugia, Italy
  • Universidade do Porto, Portugal
  • Université Paul Sabatier - Toulouse III, France
  • Universitat de Valencia, Spain

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.

Structure

The programme is organised according to a two-year structure.

  • The first year of the programme introduces you to concepts and methods. The core of the programme is an intensive international course intended to bring all participants to a common level of excellence. It takes place in the summer between year 1 and year 2 and runs for four weeks. Coursework is taught by a select group of invited international experts.
  • The second year of the programme is devoted to tutorials covering the material dealt with in the intensive course and to a thesis project carried out in part at another university within the consortium. The intensive course is organised at the partner institutions on a rotating basis.

Department

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:

  • the design, synthesis and characterisation of new compounds (organic-inorganic, polymers).
  • the simulation of the properties and reactivity of (bio)molecules, polymers and clusters by quantum chemical and molecular modelling methods.
  • the determination of the chemical and physical properties of (bio)molecules, and polymers on the molecular as well as on the material level by spectroscopy, microscopy and other characterisation tools as related to their structure.

Objectives

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.

Career perspectives

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.



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Graduate education in Computational Science and Engineering (CMSE) at Koç University is offered through an interdisciplinary program among the Departments of the College of Arts and Sciences and the College of Engineering. Read more
Graduate education in Computational Science and Engineering (CMSE) at Koç University is offered through an interdisciplinary program among the Departments of the College of Arts and Sciences and the College of Engineering. In this program graduate students are trained on modern computational science techniques and their applications to solve scientific and engineering problems. New technological problems and associated research challenges heavily depend on computational modeling and problem solving. Because of the availability of powerful and inexpensive computers model-based computational experimentation is now a standard approach to analysis and design of complex systems where real experiments can be expensive or infeasible. Graduates of the CMSE Program should be capable of formulating solutions to computational problems through the use of multidisciplinary knowledge gained from a combination of classroom and laboratory experiences in basic sciences and engineering. Individuals with B.S. degrees in biology, chemistry, physics, and related engineering disciplines should apply for graduate study in the CMSE Program.

Current faculty projects and research interests:

• Computational Biology & Bioinformatics
• Computational Chemistry
• Computational Physics
• Molecular Dynamics and Simulation
• Parallel and High Performance Computing
• Computational Fluid Dynamics
• Dynamical and Stochastic Systems
• Quantum Mechanics of Many Body Systems
• Electronic Design Automation
• Numerical Methods
• Simulation of Material Synthesis
• Structural Dynamics
• Biomedical Modeling and Simulation
• Virtual Environments

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Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling. Read more
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling.

We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.

You master these areas through studying topics including:
-Non-linear and evolutionary computational methods for derivatives pricing and portfolio management
-Applications of calculus and statistical methods
-Computational intelligence in finance and economics
-Financial markets

You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

This course is also available on a part-time basis.

Professional accreditation

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.

Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
-HSBC
-Mitsubishi UFJ Securities
-Old Mutual
-Bank of England

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-CCFEA MSc Dissertation
-Financial Engineering and Risk Management
-Introduction to Financial Market Analysis
-Learning and Computational Intelligence in Economics and Finance
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Big-Data for Computational Finance (optional)
-Industry Expert Lectures in Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Programming in Python (optional)
-Artificial Neural Networks (optional)
-High Frequency Finance and Empirical Market Microstructure (optional)
-Machine Learning and Data Mining (optional)
-Trading Global Financial Markets (optional)
-Creating and Growing a New Business Venture (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Constraint Satisfaction for Decision Making (optional)

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Study a degree which develops your arts practice through the expressive world of creative computation. It provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition. Read more

Study a degree which develops your arts practice through the expressive world of creative computation. It provides you with the historical foundations, frameworks and critical skills to produce a series of projects for public exhibition. It is delivered by Computing.

What is computational art?

Computation consists of all the changes brought about by digital technology. Art is an open set of ways of acting inventively in culture. Mixing the two together in a systematic way gives us computational art. This is a very open field, and one that is set to expand enormously in the coming years. It is where the most exciting developments in technology and in culture can already be found. This degree will place you in the middle of this fast-evolving context.

What will I learn?

This degree develops your arts practice through the expressive world of creative computation. Over a year (full-time) or two years (part-time) you will develop your artistic work and thinking through the challenge of developing a series of projects for public exhibition which will explore the technological and cultural ramifications of computation. 

You will learn the fundamentals of programming and how to apply this knowledge expressively. You will work with popular open source programming environments such as Processing, OpenFrameworks, P5.js and Arduino, and will learn how to program in languages such as Java, Javascript and C++. 

Since computational artworks don’t necessarily involve computers and screens, we also encourage students to produce works across a diverse range of media. Supported by studio technicians in state-of-the-art facilities, our students are producing works using tools such as 3D printers, laser cutters, robotics, wearable technologies, paint, sculpture and textiles. 

You will also study contextual modules on computational art and the socio-political effects of technology. These modules provide students with the historical foundations, frameworks, critical skills and confidence to express their ideas effectively. You will have the opportunity to learn the cultural histories of technology, to reflect on computation in terms of its wider cultural effects, and to understand the way in which art provides rigorous ways of thinking. 

Through our masterclass series, we regularly invite world-class artists and curators to explain their work and engage in critical dialogue with the students. This allows you to develop a wider understanding of the contemporary art scene and how your work sits within the professional art world.

MA or MFA Computational Arts?

As well as the MA, we also offer an MFA in Computational Arts. The MA is 1 year (full-time), the MFA 2 years (full-time).

The first year of the MFA is identical to the MA. You take the same classes and you learn the same things. The differences between the two courses is that in the MFA you get a 2nd year in which you take additional courses which help you develop your arts practice further. These courses mean that you get a space to work under a tutor's supervision. 



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

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 previously offered include (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)
  • Numerical Methods for Stochastic Differential Equations (5 credits, semester 2)
  • Research-Linked Topics (10 credits, semesters 1 and 2)

Additional compulsory courses for Computational Stream previously offered include:

  • Numerical Partial Differential Equations (10 credits, semester 2)
  • Time Series (10 credits, semester 2)

Additional compulsory courses for Financial stream previously offered include:

  • Financial Risk Theory (10 credits, semester 2)
  • Optimization Methods in Finance (10 credits, semester 2)

Optional courses previously offered include:

  • Numerical Partial Differential Equations (10 credits, semester 2)
  • Time Series (10 credits, semester 2)
  • Financial Risk Theory (10 credits, semester 2)
  • Optimization Methods in Finance (10 credits, semester 2)
  • Integer and Combinatorial Optimization (10 credits, semester 2)
  • Bayesian Theory (10 credits, semester 1)
  • Credit Scoring (10 credits, semester 2)
  • Python Programming (10 credits, semester 1)
  • Scientific Computing (10 credits, semester 1)
  • Programming Skills - HPC MSc (10 credits, semester 1)
  • Parallel Numerical Algorithms - HPC MSc (10 credits, semester 1)
  • Applied Databases (10 credits)

Work placements/internships

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.

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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Doctorate study in Computational Physics is an opportunity to engage in rigorous scholarly pursuit, and to contribute original research to a body of academia. Read more
Doctorate study in Computational Physics is an opportunity to engage in rigorous scholarly pursuit, and to contribute original research to a body of academia.

At the School of Mathematics and Physics, you will have the opportunity to advance your knowledge of computational physics, while developing your research skills and working with specialists. Computational Physics is a fundamental area of study that underpins a vast array of topics. During your research, you may have the opportunity to develop national and international collaborations.

Research in Computational Physics covers a broad spectrum, including the distinct areas of nanostructured soft matter, active matter, materials science and molecular biophysics. You benefit from dedicated academic supervisors, in-depth training programmes and specialist computational facilities.

Research Areas, Projects & Topics

Main Research Areas:
-Nanostructured Soft Matter
-Active Matter
-Materials Science
-Molecular Biophysics

For detailed information about the School’s research activity please visit: http://www.lincoln.ac.uk/home/smp/research/

How You Study

You can benefit from specialist computational facilities, training programmes to enhance your research skills and support from dedicated academic supervisors. You will be supported and encouraged to submit papers to international scientific journals, present your findings at conferences and share knowledge with colleagues across the University.

Due to the nature of postgraduate research programmes, the vast majority of your time will be spent in independent study and research. You will have meetings with your academic supervisor, however the regularity of these will vary depending on your own individual requirements, subject area, staff availability and the stage of your programme.

How You Are Assessed

A PhD is usually awarded based on the quality of your thesis and your ability in an oral examination (viva voce) to present and successfully defend your chosen research topic.

Career and Personal Development

This research programme is designed to allow you to expand your knowledge and expertise in an area of specific interest. It provides the opportunity to develop an in-depth foundation for further research or progression to careers across the broad spectrum of computational physics-related industries and in academia.

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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. Read more

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.

Key benefits

  • An understanding of modern financial technology (FinTech) including electronic trading and distributed-ledger technology.
  • Practical hands-on techniques for working with and analysing financial data, which draw on modern developments in Artificial Intelligence and Big Data technology.
  • The opportunity to understand the practical aspects of quantitative finance and FinTech from Industry experts located in the heart of one of the World’s financial centres.

Description

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.

Career prospects

Students are expected to go in to careers such as Investment Banking, Hedge Funds and Regulatory Bodies.  

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Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling. Read more
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling.

We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.

You master these areas through studying topics including:

- Non-linear and evolutionary computational methods for derivatives pricing and portfolio management
- Applications of calculus and statistical methods
- Computational intelligence in finance and economics
- Financial markets

You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

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This course has been designed to reflect the wide applications of Computational Fluid Dynamics. Read more

This course has been designed to reflect the wide applications of Computational Fluid Dynamics. You will learn to understand, write and apply CFD methods across a wide broad range of fields, from aerospace, turbomachinery, multi-phase flow and heat transfer, to microflows, environmental flows and fluid-structure interaction problems. Tailor your course by choosing from a range of specialist modules covering application-specific methods and techniques.

Who is it for?

Designed to meet the education needs of graduates and professional engineers who are looking to kick-start an industrial or research career in the rapidly growing field of Computational Fluid Dynamics. This course bridges the gap between the introductory level of undergraduate courses and the applied expertise acquired by engineers using CFD in industry. You will gain the knowledge and appreciation of CFD methods necessary for a strong foundation to a career in this exciting engineering discipline.

Why this course?

The MSc in Computational Fluid Dynamics provides a solid background so that you will be able to apply CFD methods as a tool for design, analysis and engineering applications. With a strong emphasis on understanding and application of the underlying methods, enthusiastic students will be able to write their own CFD codes during the course.

Sharing some modules with the MSc in Aerospace Dynamics gives you the opportunity to interact with students from other disciplines. In recent years, our students have been had the opportunity for work-based placements at the Aircraft Research Association (ARA), European Space Agency (ESA), Ricardo and DAF Trucks.

Informed by Industry

Our strategic links with industry ensures that all of the materials taught on the course are relevant, timely and meet the needs of organisations competing within the computational analysis sector. This industry led education makes Cranfield graduates some of the most desirable for companies to recruit.

The Industrial Advisory Panel is comprised of senior industry professionals provides input into the curriculum in order to improve the employment prospects of our graduates.

Accreditation

The MSc in Computational Fluid Dynamics will meet, in part, the exemplifying academic benchmark requirements for registration as a Chartered Engineer. Accredited MSc graduates who also have a BEng (Hons) accredited for CEng will be able to show that they have satisfied the educational base for CEng registration.

Course details

The taught modules are delivered from October to April via a combination of structured lectures, and computer based labs.

The core part of the course consists of modules which are considered to represent the necessary foundation subject material. The course is designed to reflect the broad range of CFD applications by providing a range of optional modules to address specific application areas. Students on the part-time programme will complete all of the compulsory modules based on a flexible schedule that will be agreed with the course director.

Individual project

The taught element of the course finishes in May, at which point you will have an excellent understanding of CFD methods and applications. From May to September you will work full-time on your individual research project. The research project gives you the opportunity to produce a detailed piece of work either in close collaboration with industry, or on a particular topic which you are passionate about.

Recent Individual Research Projects include:

  • A Study of A-pillar Vortices on the Jaguar XF Using Transitional Turbulence Models
  • Aerodynamic Analysis and Optimisation of the Aegis UAV
  • Performance Analysis of Hypervapotron Inlet Region
  • Phase Separation of Oil-water Flow in a Pipe Bend
  • CFD Simulation of a Novel CO Sensor
  • Shock Wave Interaction with Biological Membranes for Drug Therapy
  • High Resolution Implicit Large Eddy Simulation of Ariane 5 Aerodynamics.

Assessment

Taught modules 50%, Individual research project 50%

Your career

Strategic industrial links ensure that the course meets the needs of the organisations competing within the computational sector therefore making our graduates some of the most desirable in the world for companies to recruit. An increasing demand for CFD specialists with in depth technical knowledge and practical skills within a wide range of sectors has seen our graduates employed by leading companies including:

  • Alstom
  • BAE Systems
  • Cummins Turbo Technology
  • BHR
  • ESTEC
  • Hindustan Aeronautics Ltd
  • NUMECA
  • ONERA
  • Rio Tinto
  • Rolls-Royce plc
  • Siemens.

Roughly one third of our graduates go on to register for PhD degrees, many on the basis of their MSc individual research project. Thesis topics are often supplied by individual companies on in-company problems with a view to employment after graduation - an approach that is being actively encouraged by a growing number of industries.




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