Masters Degrees (Computational Modelling)

Our highly sought-after graduates benefit from a programme that integrates training in identifying, framing and effectively researching social problems with a leading computational approach to social science.

Furthermore, we are home to the Centre for Research in Social Simulation (CRESS) and its world-leading expertise in agent-based modelling.

PROGRAMME OVERVIEW

Interest in simulation has grown rapidly in the social sciences. New methods have been developed to tackle this complexity. This programme will integrate traditional and new methods, to model complexity, evolution and the adaptation of social systems.

These new methods are having an increasing influence on policy research through a growing recognition that many social problems are insufficiently served by traditional policy modelling approaches.

The Masters in Social Science and Complexity will equip you to develop expertise in the methods necessary to tackle complex, policy-relevant, real-world social problems through a combination of traditional and computational social science methods, and with a particular focus on policy relevance.

PROGRAMME STRUCTURE

This programme is studied full-time over one academic year and part-time over two academic years. It consists of eight taught modules and a dissertation. The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
-Data Analysis
-Field Methods
-Computational Modelling
-Theory Model Data
-Modelling the Complex World
-Policy Modelling
-Theory and Method
-Statistical Modelling
-Evaluation Research
-Dissertation

EDUCATIONAL AIMS OF THE PROGRAMME

The main aims of the programme are to:
-Provide an appropriate training for students preparing MPhil/PhD theses, or for 
 students going on to employment involving the use of social science and policy research
-Provide training that fully integrates social science, policy modelling and computational methodologies to a high standard
-Provide training resulting in students with high quality analytic, methodological, computational and communication skills

PROGRAMME LEARNING OUTCOMES
The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:
-Develop skills in tackling real world policy problems with creativity and sound methodological judgment
-Cover the principles of research design and strategy, including formulating research 
questions or hypotheses and translating these into practicable research designs and models
-Introduce students to the methodological and epistemological issues surrounding research in the social sciences in general and computational modelling in particular
-Develop skills in programming in NetLogo for the implementation of agent-based models for the modelling of social phenomena
-Develop skills in the acquisition and analysis of social science data
-Make students aware of the range of secondary data available and equip them to evaluate its utility for their research
-Develop skills in searching for and retrieving information, using library and Internet resources
-Develop skills in the use of SPSS, and in the main statistical techniques of data analysis, including multivariate analysis
-Develop skills in the use of CAQDAS software for the analysis of qualitative data
-Develop skills in writing, in the preparation of a research proposal, in the presentation ofresearch results and in verbal communication
-Help students to prepare their research results for wider dissemination, in the form of seminar papers, conference presentations, reports and publications, in a form suitable for a range of audiences, including academics, stakeholders, policy makers, professionals, service users and the general public

Knowledge and understanding
-Show advanced knowledge of qualitative, quantitative and computational methodologies in the social science
-Show advanced knowledge of modelling methodologies, model construction and analysis
-Show critical understanding of methodological and epistemological challenges of social science and computer modelling
-Show critical awareness and understanding of the methodological implications of a range of sociological theories and approaches
-Show understanding the use and value of a wide range of different research approaches across the quantitative and qualitative spectra
-Show advanced knowledge in data collection, analysis and data driven modelling
-Show advanced knowledge of policy relevant social science research and modelling
-Show advanced understanding of the policy process and the role of social science and modelling therein
-Show advanced knowledge of statistical modelling

Intellectual / cognitive skills
-Systematically formulate researchable problems; analyse and conceptualise issues; critically appreciate alternative approaches to research; report to a range of audiences
-Conceptual development of Social Science and Complexity models to creatively enhance the understanding of social phenomena
-Integration of qualitative, quantitative and computational data
-Judgement of problem-methodology match
-Analyse qualitative and quantitative data drawn both from ‘real world’ and ‘virtual world’ environments, using basic and more advanced techniques, and draw warranted conclusions
-Develop original insights, questions, analyses and interpretations in respect of research questions
-Critically evaluate the range of approaches to research

Professional practical skills
-Formulate, design, plan, carry out and report on a complete research project
-Use the range of traditional and computational techniques employed in sociological research
-Ability to produce well founded, data driven and validated computational models
-Generate both quantitative and qualitative data through an array of techniques, and select techniques of data generation on appropriate methodological bases
-Employ a quantitative (SPSS) and qualitative software package to manage and analyse data
-Plan, manage and execute research as part of a team and as a sole researcher
-Ability to communicate research findings models in social science and policy relevant ways
-Ability to manage independent research

Key / transferable skills
-Communicate complex ideas, principles and theories by oral, written and visual means
-Apply computational modelling methodology to complex social issues in appropriate ways
-Creativity in approaching complex problems and a the ability of communicating and justifying problem solutions
-Apply computing skills for computational modelling, research instrument design, data analysis, and report writing and presentation
-Work to deadlines and within work schedules
-Work independently or as part of a team
-Demonstrate experience of a work environment

PLACEMENTS

On the MSc Social Science and Complexity, we offer the opportunity to take a research placement during the Easter vacation. This will provide you with first-hand experience of real-life policy research in action.

Organisations in which placements might be possible are a number of consultancies (e.g. Sandtable), government departments (e.g. Defra) and academic research centres (e.g. Centre for Policy Modelling at Manchester).

CAREER OPPORTUNITIES

Computational methods and especially computer-based simulations, are becoming increasingly important in academic social science and policy making.

Graduates might find career opportunities in government departments, consultancies, government departments, consultancies, NGOs and academia.

GLOBAL OPPORTUNITIES

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

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

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

Key Features of Erasmus Mundus Computational Mechanics MSc

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

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

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

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

Modules

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

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

Accreditation

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

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

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

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

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

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

Links with Industry

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

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

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

Careers

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

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

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



Student Quotes

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

Prabhu Muthuganeisan, MSc Computational Mechanics

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* Subject to validation, 2017 entry

Liverpool Hope’s MSc Computer Science is a research-informed, academically rigorous course and is designed to provide a flexible, purposeful and challenging set of coherent courses to meet scientific, industrial and employment challenges in this fast-evolving technological area. Graduates will have developed scientific and analytical skills which are highly valued in the computing, engineering, IT and business industries.

The course offers a mix of compulsory and elective courses, and a research dissertation, so you can focus your skill base and your potential career direction.

The course has been designed with employability in mind, whether it is within IT industry or as a function of other sectors, scientific computing and technical skills are in great demand and therefore highly valued. There are opportunities for placements and enterprise development.

Curriculum

The MSc Computer Science combines academic and practical course, consisting of eight taught courses (four compulsory and four elective) and a dissertation (final research project).

The Compulsory courses are:

· Computational Modelling and Simulation

· Algorithms

· Innovations in Computer Science

· Research Methods for Computer Science

· Dissertation for MSc Computer Science

Elective courses include:

· Embedded Systems and Robotics

· Cloud Computing and Web Services

· Mobile and Ubiquitous Computing

· Human Computer Interaction

· E-Business

Course Descriptions

· Computational Modelling and Simulation (compulsory – 15 credits): This course develops understanding and knowledge of the principles, techniques and design of computational modelling and their applications.

· Algorithms (compulsory - 15 credits): This course gives a firm grounding in the philosophy and evolution of algorithmic design and analysis for computer science, engineering and information systems.

· Innovations in Computer Science (compulsory - 15 credits): You will examine the particular research interests of Computer Science Department.

· Research Methods for Computer Science (compulsory - 15 credits): The course will expose you to the established techniques of research and enquiry that are used to extend, create and interpret knowledge in computer science

· Embedded Systems and Robotics (elective - 15 credits): This course will examine the Robotics Operating System and robotic programming languages, such as Urbi.

· Cloud Computing and Web Services (elective - 15 credits): You will study the concepts behind the idea of cloud computing and web services and gain practical knowledge of Azure, the .Net framework and C#.

· Mobile and Ubiquitous Computing (elective - 15 credits): You will examine mobile phone OSs (Android) and Windows Phone 7. You will learn how to develop software for these devices using JavaFX and C#/Silverlight.

· Human Computer Interaction (elective - 15 credits): Human computer interaction (HCI) is the study of interaction between people and computers and is the most multi-disciplinary module available in the MSc Computer Science.

·
* E-Business (elective - 15 credits): E-business encompasses, and is more than, e-commerce. You will examine e-commerce technology, such as the internet and web-based technologies.

· Dissertation for MSc Computer Science (compulsory - 60 credits): This module will allow the students to develop a Masters level research project with the support of an academic supervisor.

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

This MRes in Computer Modelling in Engineering programme consists of two streams: students may choose to specialise in either structures or fluids. The taught modules provide a good grounding in computer modelling and in the finite element method, in particular.

Key Features of MRes in Computer Modelling in Engineering

Computer simulation is now an established discipline that has an important role to play in engineering, science and in newly emerging areas of interdisciplinary research.

Using mathematical modelling as the basis, computational methods provide procedures which, with the aid of the computer, allow complex problems to be solved. The techniques play an ever-increasing role in industry and there is further emphasis to apply the methodology to other important areas such as medicine and the life sciences.

The Zienkiewicz Centre for Computational Engineering, within which this course is run, has excellent computing facilities, including a state-of-the-art multi-processor super computer with virtual reality facilities and high-speed networking.

This Computer Modelling in Engineering course is suitable for those who are interested in gaining a solid understanding of computer modelling, specialising in either structures or fluids, and taking the skills gained through this course to develop their career in industry or research.

If you would like to qualify as a Chartered Engineer, this course is accredited with providing the additional educational components for the further learning needed to qualify as a Chartered Engineer, as set out by UK and European engineering professional institutions.

Modules

Modules on the Computer Modelling in Engineering programme typically include:

• Finite Element and Computational Analysis
• Numerical Methods for Partial Differential Equations
• Solid Mechanics
• Advanced Fluid Mechanics
• Dynamics and Transient Analysis
• Communication Skills for Research Engineers
• MRes Research Project

Accreditation

The MRes Computer Modelling in Engineering 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).

The MRes Computer Modelling in Engineering 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.

The MRes Computer Modelling in Engineering 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

The Civil and Computational Engineering Centre has an extensive track record of industrial collaboration and contributes to many exciting projects, including the aerodynamics for the current World Land Speed Record car, Thrust SSC, and the future BLOODHOUND SSC, and the design of the double-decker super-jet Airbus A380.

Examples of recent collaborators and sponsoring agencies include: ABB, Audi, BAE Systems, British Gas, Cinpress, DERA, Dti, EADS, EPSRC, European Union, HEFCW, HSE, Hyder, Mobil, NASA, Quinshield, Rolls-Royce, South West Water, Sumitomo Shell, Unilever, US Army, WDA.

Student Quotes

“I was attracted to the MRes course at Swansea as the subject matter was just what I was looking for.

I previously worked as a Cardiovascular Research Assistant at the Murdoch Children’s Research Institute in Melbourne. My employer, the Head of the Cardiology Department, encouraged me to develop skills in modelling as this has a lot of potential to help answer some current questions and controversies in the field. I was looking for a Master’s level course that could provide me with computational modelling skills that I could apply to blood flow problems, particularly those arising from congenital heart disease.

The College of Engineering at Swansea is certainly a good choice. In the computational modelling area, it is one of the leading centres in the world (they wrote the textbook, literally). A lot of people I knew in Swansea initially came to study for a couple of years, but then ended up never leaving. I can see how that could happen.”

Jonathan Mynard, MRes Computer Modelling in Engineering, then PhD at the University of Melbourne, currently post-doctoral fellow at the Biomedical Simulation Laboratory, University of Toronto, Canada

Careers

Employment in a wide range of industries, which require the skills developed during the Computer Modelling in Engineering course, from aerospace to the medical sector. Computational modelling techniques have developed in importance to provide solutions to complex problems and as a graduate of this course, you will be able to utilise your highly sought-after skills in industry or research.

Research

The Research Excellence Framework (REF) 2014 ranks Engineering at Swansea as 10th in the UK for the combined score in research quality across the Engineering disciplines.

World-leading research

The REF shows that 94% of research produced by our academic staff is of World-Leading (4*) or Internationally Excellent (3*) quality. This has increased from 73% in the 2008 RAE.

Research pioneered at the College of Engineering harnesses the expertise of academic staff within the department. This ground-breaking multidisciplinary research informs our world-class teaching with several of our staff leaders in their fields.

Highlights of the Engineering results according to the General Engineering Unit of Assessment:

Research Environment at Swansea ranked 2nd in the UK
Research Impact ranked 10th in the UK
Research Power (3*/4* Equivalent staff) ranked 10th in the UK

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Mathematical Biology at Dundee

The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. In his famous book On Growth and Form (where he applied geometric principles to morphological problems) Thompson declares:

"Cell and tissue, shell and bone, leaf and flower, are so many portions of matter, and it is in obedience to the laws of physics that their particles have been moved, molded and conformed. They are no exceptions to the rule that God always geometrizes. Their problems of form are in the first instance mathematical problems, their problems of growth are essentially physical problems, and the morphologist is, ipso facto, a student of physical science."

Current mathematical biology research in Dundee continues in the spirit of D'Arcy Thompson with the application of modern applied mathematics and computational modelling to a range of biological processes involving many different but inter-connected phenomena that occur at different spatial and temporal scales. Specific areas of application are to cancer growth and treatment, ecological models, fungal growth and biofilms. The overall common theme of all the mathematical biology research may be termed"multi-scale mathematical modelling" or, from a biological perspective, "quantitative systems biology" or"quantitative integrative biology".

The Mathematical Biology Research Group currently consists of Professor Mark Chaplain, Dr. Fordyce Davidson and Dr. Paul Macklin along with post-doctoral research assistants and PhD students. Professor Ping Lin provides expertise in the area of computational numerical analysis. The group will shortly be augmented by the arrival of a new Chair in Mathematical Biology (a joint Mathematics/Life Sciences appointment).

As a result, the students will benefit directly not only from the scientific expertise of the above internationally recognized researchers, but also through a wide-range of research activities such as journal clubs and research seminars.

Aims of the programme

1. To provide a Masters-level postgraduate education in the knowledge, skills and understanding of mathematical biology.
2. To enhance analytical and critical abilities and competence in the application of mathematical modeling techniques to problems in biomedicine.

Prramme Content

This one year course involves taking four taught modules in semester 1 (September-December), followed by a further 4 taught modules in semester 2 (January-May), and undertaking a project over the Summer (May-August).

A typical selection of taught modules would be:

Dynamical Systems
Computational Modelling
Statistics & Stochastic Models
Inverse Problems
Mathematical Oncology
Mathematical Ecology & Epidemiology
Mathematical Physiology
Personal Transferable Skills

Finally, all students will undertake a Personal Research Project under the supervision of a member of staff in the Mathematical Biology Research Group.

Methods of Teaching

The programme will involve a variety of teaching formats including lectures, tutorials, seminars, journal clubs, case studies, coursework, and an individual research project.

Taught sessions will be supported by individual reading and study.

Students will be guided to prepare their research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

Career Prospects

The Biomedical Sciences are now recognizing the need for quantitative, predictive approaches to their traditional qualitative subject areas. Healthcare and Biotechnology are still fast-growing industries in UK, Europe and Worldwide. New start-up companies and large-scale government investment are also opening up employment prospects in emerging economies such as Singapore, China and India.

Students graduating from this programme would be very well placed to take advantage of these global opportunities.

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Aerospace engineering has evolved and diversified since the early days of powered flight. Employers now require skills ranging from aerodynamics and flight control to space engineering simulation and design. This diversity means that engineers need to be able to operate and develop advanced devices, and understand complex theoretical and computational models.

* This programme will give you advanced skills in computational modelling, numerical techniques and an in-depth understanding in engineering approaches to aerospace problems
* After your degree, you will be well prepared to develop new computational and technological products for the aerospace industries
* You will join research groups working at the cutting edge of aerospace engineering, and computational modelling
* This is a well established course with variety and choice for students - there are a wide number of engineering modules, but also the chance to specialise on your own area

Why study with us?

The School of Engineering and Materials Science (SEMS) undertakes high quality research in a wide range of areas. This research feeds into our teaching at all levels, helping us to develop very well qualified graduates with opportunities for employment both in many leading industries as well as in research. Both Engineering and Materials are very well established at Queen Mary, with the Aerospace Department being the first established in the UK. Our aerospace teaching programmes were ranked number 2 in the UK in the 2011 National Student Survey.

Studying Engineering has taught me to think, plan, organise and execute tasks in a systematic and methodical manner. Osman Bawa

* This MSc programme is available to students from a variety of non-engineering backgrounds such as Physics, Maths, and Electronic Engineering
* It was the first of its kind in the country; offering some unique modules including, Aeroelasticity, Crash worthiness, and Space engineering
* Students will collaborate with researchers working in alternative fuels sources, so it is relevant and timely
* Aerospace Engineering is an employment related field which allows you to keep up-to-date with the latest developments in design, aerodynamics, propulsion and technology.

Facilities

You will have access to a range of facilities, including:

* Excellent computing resources such as a high-performance computing cluster, several high-performance PC clusters and parallel high-performance SGI computer clusters, an extensive unit of Linux and UNIX workstations.
* A wide range of experimental facilities from low speed wind tunnels with one of the lowest ever recorded turbulence level of 0.01% to supersonic wind tunnels, anechoic chamber dedicated to aeroacoustics problems, two new state-of-the-art electrospray technology laboratories, experimental propulsion, an advanced CueSim flight simulator and labs equipped with modern measurements techniques.
* Engineering and Materials Sciences postgraduates will also have access to the School's extensive experimental facilities used for materials, the latest electron microscopes and a brand new Nanovision centre.

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The Masters in Civil Engineering & Management introduces you to contemporary business and management issues while increasing your depth of knowledge in your chosen civil engineering speciality.

Why this programme

◾Civil engineering at the University of Glasgow is ranked 4th in the UK and 1st in Scotland (Guardian University Guide 2017).
◾With a 93% overall student satisfaction in the National Student Survey 2016, Civil Engineering at Glasgow continues to meet student expectations combining both teaching excellence and a supportive learning environment.
◾The University has a long history of research in Civil Engineering. The UK's first Chair of Civil Engineering was established at the University in 1840 and early occupants such as William J. M. Rankine set a research ethos that has endured.
◾You will be taught jointly by staff from the School of Engineering and the Adam Smith Business School. You will benefit from their combined resources and expertise and from an industry-focused curriculum.
◾If you are a graduate engineer looking to broaden your knowledge of management while also furthering your knowledge of civil engineering, this innovative programme is designed for you.
◾You will gain first-hand experience of managing an engineering project through the integrated systems design project, allowing development of skills in project management, quality management and costing.
◾You will be able to apply management to engineering projects, allowing you to gain an advantage in today’s competitive job market and advance to the most senior positions within an engineering organisation.
◾This programme has a September and January intake.

Programme structure

There are two semesters of taught material and a summer session during which you will work on an individual supervised project and write a dissertation on its outcomes. Students entering the programme in January are restricted to civil engineering (i.e. excluding management) topics only.

Semester 1

You will be based in the Adam Smith Business School, developing knowledge and skills in management principles and techniques. We offer an applied approach, with an emphasis on an informed critical evaluation of information, and the subsequent application of concepts and tools to the core areas of business and management.
◾Contemporary issues in human resource management
◾Managing creativity and innovation
◾Managing innovative change
◾Marketing management
◾Operations management
◾Project management.

Semester 2

You will study engineering courses, which aim to enhance your group working and project management capability at the same time as improving your depth of knowledge in chosen civil engineering subjects.
◾Integrated systems design project.

Optional courses

Select a total of 4 courses from Lists A and B, at least 1 must be from List A:

List A

◾Advanced soil mechanics 5
◾Advanced structural analysis and dynamics 5
◾Computational modelling of non-linear problems 5
◾Introduction to wind engineering
◾Principles of GIS.

List B

◾Geotechnical engineering 3
◾Ground engineering 4
◾Recycling urban land
◾Structural analysis 4
◾Transportation systems engineering 4.

Project or dissertation

You will undertake an individual project or dissertation work in the summer period (May–August). This will give you an opportunity to apply and consolidate the course material and enhance your ability to do independent work, as well as present results in the most appropriate format. Project and dissertation options are closely linked to staff research interests. September entry students have a choice of management dissertation topics in addition to civil engineering projects, and January entry students have a choice of civil engineering projects.

Projects

There are two semesters of taught material and a summer session during which you will work on an individual supervised project and write a dissertation on its outcomes. Students entering the programme in January are restricted to civil engineering (i.e. excluding management) topics only.

Semester 1

You will be based in the Adam Smith Business School, developing knowledge and skills in management principles and techniques. We offer an applied approach, with an emphasis on an informed critical evaluation of information, and the subsequent application of concepts and tools to the core areas of business and management.
◾Contemporary issues in human resource management
◾Managing creativity and innovation
◾Managing innovative change
◾Marketing management
◾Operations management
◾Project management.

Semester 2

You will study engineering courses, which aim to enhance your group working and project management capability at the same time as improving your depth of knowledge in chosen civil engineering subjects.
◾Integrated systems design project.

Optional courses

Select a total of 4 courses from Lists A and B, at least 1 must be from List A:

List A
◾Advanced soil mechanics 5
◾Advanced structural analysis and dynamics 5
◾Computational modelling of non-linear problems 5
◾Introduction to wind engineering
◾Principles of GIS.

List B
◾Geotechnical engineering 3
◾Ground engineering 4
◾Recycling urban land
◾Structural analysis 4
◾Transportation systems engineering 4.

Project or dissertation

You will undertake an individual project or dissertation work in the summer period (May–August). This will give you an opportunity to apply and consolidate the course material and enhance your ability to do independent work, as well as present results in the most appropriate format. Project and dissertation options are closely linked to staff research interests. September entry students have a choice of management dissertation topics in addition to civil engineering projects, and January entry students have a choice of civil engineering projects.

Industry links and employability

◾The programme makes use of the combined resources and complementary expertise of the civil engineering and business school staff to deliver a curriculum which is relevant to the needs of industry.
◾You, as a graduate of this programme, will be capable of applying the extremely important aspect of management to engineering projects allowing you to gain an advantage in today’s competitive job market and advance to the most senior positions within an engineering organisation.
◾The School of Engineering has extensive contacts with industrial partners who contribute to several of their taught courses, through active teaching, curriculum development, and panel discussion. Recent contributions in Civil Engineering include: Arup and Mott MacDonald.
◾During the programme students have an opportunity to develop and practice relevant professional and transferable skills, and to meet and learn from employers about working in the civil engineering industry.

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This postgraduate degree studies the cognitive processes and representations underlying human thought, knowledge and behaviour. It integrates a wide range of disciplines and methodologies with the core assumption that human cognition is a computational process, implemented in neural hardware.

Key topics include: the nature of computational explanation; general principles of cognition; methodology of computational modelling; theories of the cognitive architecture; symbol systems; connectionism; neural computation; and case studies in computational cognitive modelling.

The programme involves intensive training in experimental design and methodology, building computational models and carrying out a substantial piece of original research.

Why study this course at Birkbeck?

Draws on academics from many disciplines, including internationally renowned researchers in psychology, computational modelling and neuroscience.
Good foundation for a research career in the cognitive sciences.
Develops an understanding of core theoretical principles of human thought and an expertise in computer simulation.
Designed for graduates of either the computational sciences or the psychological sciences.
The Department of Psychological Sciences has an outstanding research tradition, with an outstanding international reputation in all aspects of cognitive neuroscience, and especially developmental cognitive neuroscience.
You will have the opportunity to interact with world-class researchers in cognitive neuroscience and cognitive neuropsychology, and attend research seminars organised by the department and a number of other local research centres and institutes.
Psychological Sciences at Birkbeck were ranked 5th in the UK in the 2014 Research Excellence Framework (REF) and we achieved 100% for a research environment conducive to research of world-leading quality.
Psychological research at Birkbeck has ranked 5th in the world in a category of the Best Global Universities Rankings 2016, an important and influential index of research quality.

Our research

Birkbeck is one of the world’s leading research-intensive institutions. Our cutting-edge scholarship informs public policy, achieves scientific advances, supports the economy, promotes culture and the arts, and makes a positive difference to society.

Birkbeck’s research excellence was confirmed in the 2014 Research Excellence Framework, which placed Birkbeck 30th in the UK for research, with 73% of our research rated world-leading or internationally excellent.

Psychological Sciences at Birkbeck were rated 5th in the UK in the 2014 Research Excellence Framework (REF) and we achieved 100% for a research environment conducive to research of world-leading quality.

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Those who study the Masters in Civil Engineering will gain advanced knowledge and associated analytical and problem-solving skills in a range of key sub-disciplines of Civil Engineering, and develop the ability to apply this knowledge in engineering design and to the solution of open-ended and multi-disciplinary problems. The MSc in Civil Engineering is intended for students with a first degree in Civil Engineering or a closely related discipline who wish to extend their expertise to a higher level in preparation for a professional career.

Why this programme

◾Civil engineering at the University of Glasgow is ranked 4th in the UK and 1st in Scotland (Guardian University Guide 2017).
◾The University of Glasgow’s School of Engineering has been delivering engineering education and research for more than 150 years and is the oldest School of Engineering in the UK.
◾You will select courses from key sub-disciplines of Civil Engineering, notably structural engineering, geotechnical engineering, environmental engineering, computational mechanics and transportation engineering.
◾With all lecture courses selected from sets of options, you can choose to develop a degree of specialization in a given sub-discipline or to remain broad-based, thus tailoring the programme to suit your interests and career aspirations.
◾Two major design project courses will develop your abilities to apply your knowledge of Civil Engineering to design of engineering projects. One of these projects is specifically civil engineering in content, but the other is multi-disciplinary in nature and will also involve MSc students from other engineering disciplines, working in teams to tackle a broad-based design problem.
◾You will also undertake an individual project, allowing you to investigate a specific topic in considerable depth.
◾You will be taught by staff who are leading researchers in their fields, so that course content can reflect state-of-the-art understanding, relevant to future challenges for civil engineering industry and the profession.
◾The programme is designed to provide the advanced education required of civil engineers of tomorrow.
◾With a 93% overall student satisfaction in the National Student Survey 2016, Civil Engineering at Glasgow continues to meet student expectations combining both teaching excellence and a supportive learning environment.

Programme structure

Modes of delivery of the MSc Civil Engineering include lectures, tutorials, design classes and computing labs, and give you the opportunity to take part in team design projects, other coursework and project-based activities, and a major individual project.

Core courses
◾Civil design project
◾Integrated systems design project.

Optional courses

Select a total of 8 courses, at least 5 of which must be from List A:

List A
◾Advanced soil mechanics 5
◾Advanced structural analysis and dynamics 5
◾Applied engineering mechanics 4
◾Computational modelling of non-linear problems 5
◾Introduction to wind engineering
◾Principles of GIS
◾Reclamation of contaminated land 5
◾Structural concrete C5.

List B
◾Environmental biotechnology 4
◾Geotechnical engineering 4
◾Ground engineering 4
◾Renewable energy 4
◾Structural analysis 4
◾Structural design 4
◾Transportation systems engineering 4.

Projects

◾To complete the MSc degree you must undertake an individual project worth 60 credits.
◾Projects can involve laboratory work, computational modelling, fieldwork, theoretical development, design or a study of industry application.
◾The project is an important part of your MSc where you can apply your newly learned skills and show to future employers that you have been working on cutting edge projects relevant to industry.
◾Your project is completed under the supervision of an academic staff member. You can choose a topic from a list of MSc projects in Civil Engineering. Alternatively, should you have your own idea for a project, staff members are always open to discussion of topics.

Example projects

Examples of projects can be found online

*Posters shown are for illustrative purposes

Industry links and employability

◾The School of Engineering has extensive contacts with industrial partners who contribute to several of the taught courses, through active teaching, curriculum development, and panel discussion.
◾The two design projects courses represent the types of projects undertaken in industry, and typically there will be input from industry practitioners in setting up the projects used in these courses.
◾Some MSc individual projects will involve interaction with industry.

Career prospects

Career opportunities include positions in civil engineering, structural engineering and environmental engineering, and working with design consultants, contractors and public authorities or utilities.

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Understanding all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.
At present, there are many sensors and actuators in every device – so they may become embedded in a physical reality. For robots that move around in a specific setting there is a pressing need for the development of proper methods of control and joint-action. The embedded, embodied nature of human cognition is an inspiration for this, and vice versa. Computational modelling of such tasks can give insight into the nature of human mental processing. In the Master’s specialisation in Robot Cognition you’ll learn all about the sensors, actuators and the computational modelling that connects them.
Making sense of sensor data – developing artificial perception – is no trivial task. The perception, recognition and even appreciation of sound stimuli for speech and music (i.e. auditory scene analysis) require modelling and representation at many levels and the same holds for visual object recognition and computer vision. In this area, vocal and facial expression recognition (recognition of emotion from voices and faces) is a rapidly growing application area. In the area of action and motor planning, sensorimotor integration and action, there are strong links with research at the world-renowned Donders Centre for Cognition.
At Radboud University we also look beyond the technical side of creating robots that can move, talk and interpret emotions as humans do. We believe that a robot needs to do more than simply function to its best ability. A robot that humans distrust will fail even if it is well programmed. Culture also plays a role in this; people in Japan are more open to the possibilities of robots than in, for example, the Netherlands. We will teach you how to evaluate humans’ attitudes towards a robot in order to use that information to create robots that will be accepted and trusted and therefore perform even better.

See the website http://www.ru.nl/masters/ai/robot

Why study Robot Cognition at Radboud University?

- We offer a great mix of technical and social aspects of robot cognition.

- This programme focuses on programming robot behaviours and evaluating them rather than building the robots themselves. We teach you to programme robots that will be used in close contact with human beings, for example in healthcare and education, rather than in industry.

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- Together with the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You could also cooperate with the Behavioural Science Institute and work in its Virtual Reality Laboratory, which can be used to study social interaction between humans and avatars.

An example of a possible thesis subject:
- Engaging human-robot interactions in healthcare for children and/or the elderly
Social robots are often deployed with 'special' user groups such as children and elderly people. Developing and evaluating robot behaviours for these user groups is a challenge as a proper understanding of their cognitive and social abilities is needed. Depending on the task, children for example need to be engaged and encouraged in a different way than adults do. What are effective robot behaviours and strategies to engage children and/or elderly people? How can these robot behaviours be evaluated in a proper way?

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Philips, Siemens, Honda, Mercedes, Google. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Robot Cognition could get:
- PhD Researcher on Cognitive-Affective Modelling for Social Robots
- PhD Researcher on Automatic analysis of human group behaviour in the presence of robots
- PhD Researcher on Automatic analysis of affective quality of conversations in human-robot interaction
- Advisor and innovation manager in the healthcare industry
- Social robotics and affective computing for robots expressing emotions
- Developer of control algorithms for using optic flow in drones
- Advisor for start-up company on developing new uses for tactile displays
- Team member in design of emotion recognition and training for autistic children

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Finland and the United States.

See the website http://www.ru.nl/masters/ai/robot

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There is a growing need for qualified professionals with expertise in environmental modelling. The UCL Environmental Modelling MSc is a cross-disciplinary degree that provides rigorous technical and scientific training for the next generation of environmental modelling professionals.

Degree information

You will gain a well-rounded training in the role, implementation and application of models in environmental science. Core modules provide a critical perspective on model-based science, and introduce essential computational and numerical methods. The programme is contextualised with reference to the challenges of understanding both natural and human-induced changes to a variety of environmental systems.

Students take modules to the value of 180 credits. The programme consists of four core modules (60 credits), optional modules (60 credits) and a research dissertation (60 credits). A Postgraduate Diploma (120 credits, full-time nine months, part-time two years) is offered. A Postgraduate Certificate (60 credits, full-time 12 weeks, part-time one year) is offered.

Core modules
-Models in Environmental Science
-Global Environmental Change
-Scientific Computing
-Analytical and Numerical Methods

Optional modules - options may include:
-Climate Modelling
-Coastal Change
-Environmental GIS
-Impacts of Climate Change on Hydro-Ecological Systems
-Lakes
-Ocean Circulation and Climate Change
-Surface Water Modelling
-Terrestrial Carbon: Monitoring and Modelling
-Other MSc modules offered across UCL may be taken at the discretion of the MSc convenor

Dissertation/report
All students undertake an independent research project, culminating in a dissertation of approximately 12,000 words and an oral presentation.

Teaching and learning
The programme is delivered through a combination of lectures, seminars, tutorials, and laboratory and computer-based practical classes. Assessment is through independent project work, practical-based and written coursework, written examinations and the dissertation.

Careers

The programme has been designed to provide an ideal foundation for PhD research, or for employment with environmental monitoring and protection agencies, industry and environmental consultancies. Graduates have gone on to careers as management consultants, business analysts and university researchers.

Top career destinations for this degree:
-Research Fellow, University of Girona and studying PhD Sanitas, Universitat de Girona (University of Girona)
-Risk Analyst, Canopius

Employability
Modelling was identified as the highest priority UK skills gap in a government review of the environmental sector. This MSc programme exposes students to the full range of environmental modelling which places graduates in a strong position to find employment. We anticipate that graduates of this MSc are either employed in the private environmental consulting sector or undertake a PhD.

Why study this degree at UCL?

The Environmental Modelling MSc is run by UCL Geography which enjoys an outstanding international reputation for its research and teaching. Research groups contributing to the MSc include those concerned with environmental modelling and observation, past climates, and recent environmental change and biodiversity.

The programme draws on the unrivalled strengths of UCL in environment modelling. Our expertise encompasses state-of-the-art global climate models, regional ocean models, advanced hydrodynamic and hydrological simulations, palaeoclimate reconstruction over geological to recent historical timescales, earth observation-derived vegetation and carbon cycle modelling, and model-based assessment of climate change impacts on coastal, estuarine and freshwater systems.

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Course Description

The course addresses the design, development, procurement, use and management of models and simulations for applications in experimentation, training, testing, analysis and assessment of military forces, systems and equipment.

Overview

On successful completion of the course you will be familiar with the technologies, methodologies, principles and terminology of Modelling and Simulation as used across defence, including the challenges and issues as well as the benefits. Through use of facilities such as the Simulation and Synthetic Environment Laboratory (SSEL), with its wide range of specialist applications, students will gain a broad understanding of modelling and simulation in areas such as training, acquisition, decision-support, analysis and experimentation.

•10 places are normally available for the full-time cohort
•The course is suitable for both military and civilian personnel, including those from defence industry and government departments

Start date: Full-time: annually in September. Part-time: by arrangement

Duration: Full-time MSc - one year, Part-time MSc - up to three years, Full-time PgCert - one year, Part-time PgCert - two years, Full-time PgDip - one year, Part-time PgDip - two years

English Language Requirements

Students whose first language is not English must attain an IELTS score of 6.5.

Course overview

The modular form of the course, consisting of a compulsory core and a selection of standard and advanced modules, enables each student to select the course of study most appropriate to their particular requirements.

Standard modules normally comprise a week of teaching (or equivalent for distance learning) followed by a further week of directed study/coursework (or equivalent for part time and distance learning).

Advanced modules, which enable students to explore some areas in greater depth, are two week (or equivalent for part time and distance learning) individual mini-projects on an agreed topic in that subject, which includes a written report and oral presentation.

- MSc students must complete a taught phase consisting of eight standard modules, which includes two core modules (Foundations of Modelling and Simulation and Networked and Distributed Simulation), plus four advanced modules, followed by an individual thesis in a relevant topic. Thesis topics will be related to problems of specific interest to students and sponsors of local industry wherever possible.

- PgDip students are required to undertake the same taught phase as the MSc, but without the individual thesis.

- PgCert students must complete the core module (Foundations of Modelling and Simulation) together with five other modules; up to three of these may be advanced modules.

Modules

Part-time students will typically not study as a cohort, but will follow an agreed individual programme of study, attending courses as convenient.
Advanced Modules, which typically comprise individual self-study, can be selected to follow on from any standard modules that have been chosen.
Standard Modules, which typically involve traditional classroom instruction and/or VLE-based delivery, can be chosen from the following:

Core:
- Foundations of Modelling and Simulation
- Networked and Distributed Simulation

Elective:
- Advanced Computer Graphics
- Advanced Discrete and Continuous Simulation
- Advanced Logistics Modelling
- Advanced Modelling and Simulation
- Advanced War Gaming and Combat Modelling
- Computational Statistics
- Computer Graphics
- Discrete and Continuous Simulation
- High Performance and Parallel Computing
- Intelligent Systems
- Intelligent Systems - Research Study
- Logistics Modelling
- Networked and Distributed Simulation Exercise
- Neural Networks
- Programming and Software Development in C
- Statistical Analysis and Trials
- War Gaming and Combat Modelling
- Weapon System Performance Assessment

Individual Project

An individual research project on an agreed topic that allows you to demonstrate your technical expertise, independent learning abilities and critical appraisal skills.

Assessment

Continuous assessment, written examinations, oral vivas and (MSc only) thesis.

Proportions of different assessment types will vary according to programme and modules taken. For an MSc these might typically comprise 15-24% continuous assessment (written and oral), 36-45% written examinations and 40% thesis/dissertation.

Career opportunities

Equips you for simulation-specific appointments within the armed forces or government, or in the defence related activities of commercial organisations.

For further information

On this course, please visit our course webpage http://www.cranfield.ac.uk/Courses/Masters/Defence-Simulation-and-Modelling

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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.

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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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 MSc provides an ideal foundation for students wishing to advance their mathematical modelling skills. The programme teaches students the basic concepts which arise in a broad range of technical and scientific problems and illustrates how these may be applied in a research context to provide powerful solutions.

Degree information

Students develop an understanding of the processes undertaken to arrive at a suitable mathematical model and are taught the fundamental analytical techniques and computational methods used to develop insight into system behaviour. The programme introduces a range of problems - industrial, biological and environmental - and associated conceptual models and solutions.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits), and a research dissertation (60 credits). The part-time option normally spans two years. The eight taught modules are spread over the two years. The research dissertation is taken in the summer of the second year.

Core modules
-Advanced Modelling Mathematical Techniques
-Nonlinear Systems
-Operational Research
-Computational and Simulation Methods
-Frontiers in Mathematical Modelling and its Applications

Optional modules
-Asymptotic Methods & Boundary Layer Theory
-Biomathematics
-Cosmology
-Evolutionary Game Theory and Population Genetics
-Financial Mathematics
-Geophysical Fluid Dynamics
-Mathematical Ecology
-Quantitative and Computational Finance
-Real Fluids
-Traffic Flow
-Waves and Wave Scattering

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of approximately 15,000-words and a project presentation.

Teaching and learning
The programme is delivered through seminar-style lectures and problem and computer-based classes. Student performance is assessed through a combination of unseen examination and coursework. For the majority of courses, the examination makes up between 90–100% of the assessment. The project is assessed through the dissertation and an oral presentation.

Careers

Our graduates have found employment in a wide variety of organisations such as Hillier-Parker, IBM, Swissbank, Commerzbank Global Equities, British Gas, Harrow Public School, Building Research Establishment and the European Centre for Medium-Range Weather-Forecasting. First destinations of recent graduates include:
-R.T.E: Engineer
-Tower Perrins: Actuarist
-Deloitte: Quantitative Analyst
-UCL: Research Associate
-C-View: Quantitative Trader
-One-to-One: Maths Tutor
-UCL Research Degree - Mathematics
-Duff & Phelps Ltd: Financial Engineer
-Bank of Tokyo Mitsubishi: Assistant Compliance Officer

Employability
The finance, actuarial and accountancy professionals are constantly in demand for high-level mathematical skills and recent graduates have taken positions in leading finance-related companies such as UBS, Royal Bank of Scotland, Societe Generale, PricewaterhouseCoopers, Deloitte, and KPMG.

In the engineering sector, recent graduates from the MSc include a mathematical modeller at Steet Davies Gleave, a leading Transportation Planning Consultancy; and a graduate trainee at WesternGreco, a business segment of Schlumberger that provides reservoir imaging, monitoring, and development services. In addition, a number of graduates have remained in education either progressing to a PhD or entering the teaching profession.

Why study this degree at UCL?

UCL Mathematics is internationally renowned for its excellent individual and group research that involves applying modelling techniques to problems in industrial, biological and environmental areas.

The department hosts a stream of distinguished international visitors. In recent years four staff members have been elected fellows of the Royal Society, and the department publishes the highly regarded research journal Mathematika.

This MSc enables students to consolidate their mathematical knowledge and formulate basic concepts of modelling before moving on to case studies in which models have been developed for issues motivated by industrial, biological or environmental considerations.

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