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Masters Degrees (Complexity Theory)

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This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. Read more
This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. During the course critical awareness of problems in information transmission, data compression and cryptography is raised, and the mathematical techniques which are commonly used to solve these problems are explored.

The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography and our academic staff include several leading researchers in these areas. Students on the programme have the opportunity to carry out their dissertation projects in cutting-edge research areas and to be supervised by experts.

The transferable skills gained during the MSc will open up a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsofcryptographyandcommunications(msc).aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and a knowledge and understanding of the subjects of cryptography and communications preparing you for research or professional employment in this area.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course former students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses as well as complete a main project under the supervision of a member of staff.

Core courses:
Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed as well as methods for obtaining confidentiality and authentication.

Channels
In this unit, you will investigate the problems of data compression and information transmission in both noiseless and noisy environments.

Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Public Key Cryptography
This course introduces some of the mathematical ideas essential for an understanding of public key cryptography, such as discrete logarithms, lattices and elliptic curves. Several important public key cryptosystems are studied, such as RSA, Rabin, ElGamal Encryption, Schnorr signatures; and modern notions of security and attack models for public key cryptosystems are discussed.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- a suitable mathematical foundation for undertaking research or professional employment in cryptography and/or communications

- the appropriate background in information theory and coding theory enabling them to understand and be able to apply the theory of communication through noisy channels

- the appropriate background in algebra and number theory to develop an understanding of modern public key cryptosystems

- a critical awareness of problems in information transmission and data compression, and the mathematical techniques which are commonly used to solve these problems

- a critical awareness of problems in cryptography and the mathematical techniques which are commonly used to provide solutions to these problems

- a range of transferable skills including familiarity with a computer algebra package, experience with independent research and managing the writing of a dissertation.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications. Read more
This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications.

You will explore the mathematical techniques that are commonly used to solve problems in the real world, in particular in communication theory and in physics. As part of the course you will carry out an independent research investigation under the supervision of a member of staff. Popular dissertation topics chosen by students include projects in the areas of communication theory, mathematical physics, and financial mathematics.

The transferable skills gained on this course will open you up to a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsforapplications.aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and knowledge and understanding of the subjects of cryptography and communications, preparing you for research or professional employment in this area.

- The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography. The academics who teach on this course include several leading researchers in these areas.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses and complete a main project under the supervision of a member of staff.

Core courses:
Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed, as well as methods for obtaining confidentiality and authentication.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- knowledge and understanding of: the principles of communication through noisy channels using coding theory; the principles of cryptography as a tool for securing data; and the role and limitations of mathematics in the solution of problems arising in the real world

- a high level of ability in subject-specific skills, such as algebra and number theory

- developed the capacity to synthesise information from a number of sources with critical awareness

- critically analysed the strengths and weaknesses of solutions to problems in applications of mathematics

- the ability to clearly formulate problems and express technical content and conclusions in written form

- personal skills of time management, self-motivation, flexibility and adaptability.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security Manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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This interdisciplinary Masters degree provides you with a broad background in some mainstream and modern aspects of mathematics and computer science. Read more

This interdisciplinary Masters degree provides you with a broad background in some mainstream and modern aspects of mathematics and computer science. You’ll be introduced to sophisticated techniques at the forefront of both disciplines.

The programme combines teaching and research from the School of Mathematics and the School of Computing. Based on the Schools’ complementary research strengths the programme follows two main strands:

  • Algorithms and complexity theory
  • Numerical methods and parallel computing

You’ll have the choice to specialise in one of these strands, gaining specialist knowledge and skills that will prepare you for a wide range of careers. You’ll also develop your research skills when you complete your dissertation.

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

Course content

It is expected that you will specialise in one of two areas during the course, although this is not essential.

The two strands are:

Algorithms and complexity theory and connections to logic and combinatorics

This concerns the efficiency of algorithms for solving computational problems, and identifies hierarchies of computational difficulty. This subject has applications in many areas, such as distributed computing, algorithmic tools to manage transport infrastructure, health informatics, artificial intelligence, and computational biology.

Numerical methods and parallel computing

Many problems, in mathematics, physics, astrophysics and biology cannot be solved using analytical techniques and require the application of numerical algorithms for progress. The development and optimisation of these algorithms coupled to the recent increase in computing power via the availability of massively parallel machines has led to great advances in many fields of computational mathematics. This subject has applications in many areas, such as combustion, lubrication, atmospheric dispersion, river and harbour flows, and many more.

For information on typical modules, read Mathematics and Computer Science MSc in the course catalogue

Learning and teaching

Teaching is carried out through a mixture of lectures and smaller group activities such as workshops. Most modules are assessed by a mix of coursework and written examinations. There is also the opportunity to complete a summer project which is individually supervised by a member of staff.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester three project is assessed by a written dissertation and a short oral presentation.

Career opportunities

Each of these areas offers many career options, and the MSc will provide you with both technical and transferrable skills, for example, conducting an extended and independent research project. It will also offer you excellent preparation for doctoral research in these or related subjects. On completion of the degree you can progress onto a wide range of opportunities including:

  • PhD in Mathematics, or in Computer Science
  • Careers in Computing and Industries which require algorithmic tools (transport infrastructure, health informatics, computational biology, artificial intelligence, companies developing the internet (e.g. search engines).
  • Many other careers (e.g. in Finance) where a mathematics background is valued.

In collaboration with both industrial and academic partners, our research has resulted in computational techniques, and software, that has been widely applied. Our industry links are extensive and include companies such as Google, Yahoo, Akamai, Microsoft, and Tracsis, as well as the NHS.

Careers support

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

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



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You should consider this programme if you are a qualified and experienced teacher, trainer or other professional working in education or training, or in a related professional field such as health. Read more
You should consider this programme if you are a qualified and experienced teacher, trainer or other professional working in education or training, or in a related professional field such as health.

The programme will develop your advanced skills in educational research methods. These include critical analysis, evidence-based inquiry, critical literature review, and quantitative and qualitative data collection and analysis.

Following a qualifying period, MPhil students can proceed to PhD studies in education and training.

Recent research projects include:

- Leadership and management in education
- Leadership in Higher Education
- Professionalism and professional practice
- Lifelong Learning
- E-Learning, social networking
- Pedagogy, learning theories and learning and teaching
- Widening participation, access, achievement and the student experience
- Creativity and complexity theory
- Childhood studies and history of education
- A range of other individually negotiated subject areas.

The aims of the programme are:

- To provide you with a doctoral programme through research study and a supervised thesis

- To provide you with an advanced knowledge of educational research methods within education, training, health and allied fields

- To help you to develop advanced skills in contemporary theoretical knowledge, critical analysis, doctoral research and evidence-based inquiry. This will enable you to make a contribution to knowledge informed by original research and scholarship.

Visit the website http://www2.gre.ac.uk/study/courses/pg/res/edu

What you'll study

Recent research projects include:

- Leadership and management in education
- Leadership in higher education
- Professionalism and professional practice
- Lifelong learning
- E-Learning, social networking
- Pedagogy, learning theories and learning and teaching
- Widening participation, access, achievement and the student experience
- Creativity and complexity theory
- Childhood studies and history of education
- A range of other individually negotiated subject areas.

Fees and finance

Your time at university should be enjoyable and rewarding, and it is important that it is not spoilt by unnecessary financial worries. We recommend that you spend time planning your finances, both before coming to university and while you are here. We can offer advice on living costs and budgeting, as well as on awards, allowances and loans.Find out more about our fees and the support available to you at our:
- Postgraduate finance pages (http://www.gre.ac.uk/finance/pg)
- International students' finance pages (http://www.gre.ac.uk/finance/international)

Assessment

Students are assessed through their research thesis.

Career options

This programme offers enhanced career opportunities in the education, training, health and allied fields.

Find out how to apply here - http://www2.gre.ac.uk/study/apply

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Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Stochastic Processes. Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Stochastic Processes: Theory and Application at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

The MRes in Stochastic Processes: Theory and Application is delivered through optional modules for the taught element followed by a large research project that contributes to the field in an explicit way, rather than merely applying existing knowledge.

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

The Department’s research groups include:

Algebra and Topology Group

Areas of interest include: Noncommutative geometry, Categorical methods in algebra and topology, Homotopy theory and homological algebra and others.

Analysis and Nonlinear Partial Differential Equations Group

Areas of interest include: Reaction-diffusion and reaction-diffusion-convection equations and systems, Navier–Stokes equations in fluid dynamic, Complexity in the calculus of variations and others.

Stochastic Analysis Group

Areas of interest include: Functional inequalities and applications, Lévy-type processes, Stochastic modelling of fractal, multi-fractal and multi-scale systems, Infinite dimensional stochastic analysis and others.

Mathematical Methods in Biology and Life Sciences Group

Areas of interest include: Mathematical pharmacology; heat and mass transfer models for plant cooling; modelling cellular signal transduction dynamics; mathematical oncology: multi-scale modelling of cancer growth, progression and therapies, and modelling-optimized delivery of multi-modality therapies; multi-scale analysis of individual-based models; spreading speeds and travelling waves in ecology; high performance computing.

Key Features

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

Course Content

As a student on the MRes Stochastic Processes programme you will study a range of topics for the taught element including:

Stochastic Calculus based on Brownian Motion

Levy processes and more general jump processes

The advanced Black-Scholes theory

Theory and numerics of parabolic differential equations

Java programming

The Stochastic Processes: Theory and Application course consists of a taught part (60 credits) and a research project (120 credits). Students will have a personal supervisor for their research project from the start of their studies.

Research projects could be of a theoretical mathematical nature, or they could be more applied, for example in financial mathematics or actuarial studies. Some of the research projects will be of an interdisciplinary character in collaboration with some of Swansea's world class engineers. For such projects it is likely that EPSRC funding would be available.

Facilities

The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use. It is a popular venue for students to work independently on the regular example sheets set by their lecturers, and to discuss Mathematics together.

Our main university library, Information Services and Systems (ISS), contains a notably extensive collection of Mathematics books.

Careers

The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistical analysis, marketing and sales.

Some of our students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where maths graduates will find plenty of career opportunities.

Research

The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.

All academic staff in Mathematics are active researchers and the department has a thriving research culture.



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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. Read more
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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Explore advanced topics in computer science with this wide-ranging programme, which will equip you with the understanding and practical skills to succeed in a variety of careers. Read more

Explore advanced topics in computer science with this wide-ranging programme, which will equip you with the understanding and practical skills to succeed in a variety of careers.

Rooted in the established research strengths of the School of Computing, the programme will introduce topics like systems programming and algorithms before allowing you to specialise through your choice of modules.

You could look at emerging approaches to human interaction with computational systems, novel architectures such as clouds, or the rigorous engineering needed to develop cutting-edge applications such as large-scale data mining and social networks.

Building on your existing knowledge of computer science, you’ll develop the theoretical and practical skills required to design and implement larger, more complex systems using state-of-the-art technologies. You’ll even have the chance to work as an integral member of one of our research groups when you develop your main project.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology. 

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as cloud computing, image analysis, machine learning, semantic technologies and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?

Take a look at the Advanced Computer Science module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • MSc Project 60 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Machine Learning 10 credits
  • Information Visualization 10 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Foundations of Modelling and Rendering 15 credits
  • Games Engines and Workflow 15 credits
  • Geometric Processing 15 credits
  • High-Performance Graphics 15 credits
  • Animation and Simulation 15 credits
  • Data Mining and Text Analytics 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science students have included:

  • iPad interaction for wall-sized displays
  • Modelling the effects of feature-based attention in the visual cortex
  • Relevance and trust in social computing for decision making
  • Energy-efficient cloud computing
  • Smart personal assistant - Ontology-enriched access to digital repositories

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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Developments in cloud computing technology are transforming the way we live and work. This programme will equip you with specialist knowledge in this fast-growing field and allow you to explore a range of advanced topics in computer science. Read more

Developments in cloud computing technology are transforming the way we live and work. This programme will equip you with specialist knowledge in this fast-growing field and allow you to explore a range of advanced topics in computer science.

You’ll gain a foundation in topics like systems programming and algorithms, as well as specialist modules in advanced distributed systems – especially cloud techniques, technologies and applications.

Building on your existing knowledge of computer science, you’ll also choose from optional modules in topics across computer science. You could look at emerging approaches to human interaction with computational systems, data mining and functional programming among others.

The programme will give you the theoretical and practical skills required to design and implement larger, more complex systems using state-of-the-art technologies. You’ll even have the chance to work as an integral member of one of our research groups when you develop your main project.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming. Throughout the year you’ll also take modules developing your understanding of cloud computing itself, from designing the high-level framework of a distributed system to big data and the “internet of things”.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, machine learning, semantic technologies and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?

Take a look at the Advanced Computer Science (Cloud Computing) module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • MSc Project 60 credits
  • Cloud Computing 15 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Machine Learning 10 credits
  • Information Visualization 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Data Mining and Text Analytics 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science (Cloud Computing) students have included:

  • Intelligent services to support sensemaking
  • Google cloud data analysis
  • Hadoop for large image management
  • Evaluating web service agreement in a cloud environment

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science. Read more

Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science.

You’ll gain a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like image analysis or text analytics, or broaden your approach with topics like cloud computing.

As one of the few schools with expertise covering text, symbolic and scientific/numerical data analysis, we can provide a breadth of expertise to equip you with a variety of skills – and you’ll work as an integral member of one of our research groups when you develop your main project. We also have close links with the Leeds Institute for Data Analytics which is at the forefront of big data research.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming, as well as the basic principles of automated reasoning, machine learning and how computers can be made to represent knowledge.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, cloud computing, semantic technologies and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?

Take a look at the Advanced Computer Science (Data Analytics) module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • Machine Learning 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • MSc Project 60 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Information Visualization 10 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Data Mining and Text Analytics 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science students have included:

  • Text mining of e-health patient records
  • Java-based visualization on ultra-high resolution displays
  • Data mining of sports performance data
  • Contour topology
  • Efficient computation for simulating tumour growths

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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From software agents used in networking systems to embedded systems in unmanned vehicles, intelligent systems are being adopted more and more often. Read more

From software agents used in networking systems to embedded systems in unmanned vehicles, intelligent systems are being adopted more and more often. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of topics in computer science.

Core modules will give you a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like bio-inspired computing or text analytics, or broaden your approach with topics like mobile app development.

You’ll gain a broad perspective on intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding and bio-computation as well as essential principles and practices in the design, implementation and usability of intelligent systems.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming, as well as the basic principles of automated reasoning, machine learning and how computers can be made to represent knowledge.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, cloud computing, graph theory and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?

Take a look at the Advanced Computer Science (Intelligent Systems) module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • MSc Project 60 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Image Analysis 15 credits

Optional modules

  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Machine Learning 10 credits
  • Intelligent Systems and Robotics 20 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science (Intelligent Systems) students have included:

  • Object-based attention in a biologically inspired network for artificial vision
  • Advanced GIS functionality for animal habitat analysis
  • Codebook construction for feature selection
  • Learning to imitate human actions

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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

Logic is the basis for reasoning about what we can express and compute, having a profound influence in philosophy, linguistics, mathematics, computer science, and electronics. Since the invention of computers, logic has always been the primary source of ideas and techniques for the theoretical and practical development of programming.

Today, as the scope of programming technologies expands, and the horizon of applications widens, research in logic and its applications in software and hardware development is booming. In industry, formal methods are an integral part of system development, e.g., in automotive electronics, avionics, and chip design.

The MRes Logic and Computation course will teach you about advanced techniques in logic and their applications in research problems in computer science. You will receive an elite education of direct relevance to research and development problems in contemporary information and communication technology (ICT).

Key Features

Teaching score of Excellent.

Highest percentage of top-class researchers of any Computer Science department in Wales – and only 12 in the UK have higher.

70% of the research activity assessed as world-leading or internationally excellent.

Our industrial programme IT Wales which can arrange vacation employment placements.

A state-of-the-art education.

Friendly staff, committed to the highest standards.

A university with high success rate, low drop-out rate, and excellent student support.

Swansea's Library spends more per student on books and other resources than any other university in Wales, and most in the UK.

Course Content

Research Component

The main part of the MRes in Logic and Computation is a substantial and challenging project involving cutting edge research. The completion of such a project will give you the ability and confidence to pursue a successful career in industrial research and development, or to proceed to academic PhD studies.

Taught Component

In seminars and reading courses you will enter the world of research by studying general topics in theoretical computer science as well as special topics for your research project. Guided by your supervisor you will conquer new technical subjects and learn to critically assess current research.

Lecturers and students will meet regularly to discuss recent developments and give informal talks. Topics of the seminars are chosen in accordance with the research projects, and will cover material such as:

Theorem proving techniques

Formal program verification

Algebraic and coalgebraic specification

Modelling of distributed systems

Advanced methods in complexity theory

Additionally you will choose selected taught modules covering important topics such as Critical Systems, IT Security, Concepts of Programming

Languages, Artificial Intelligence Applications, Design Patterns and Generic Programming.

Facilities

The Department is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

Careers

All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.

90% of Swansea’s Computer Science graduates are in full-time employment or further study within six months of graduating (HESA June 2011).

Some example job titles from the HESA survey 2011:

Software Engineer: Motorola Solutions

Change Coordinator: Logica

Software Developer/Engineer: NS Technology

Workflow Developer: Irwin Mitchell

IT Developer: Crimsan Consultants

Consultant: Crimsan Consultants

Programmer: Evil Twin Artworks

Web Developer & Web Support: VSI Thinking

Software Developer: Wireless Innovations

Associate Business Application Analyst: CDC Software

Software Developer: OpenBet Technologies

Technical Support Consultant: Alterian

Programming: Rock It

Software Developer: BMJ Group

Research

The results of the Research Excellence Framework (REF) 2014 show that Swansea Computer Science ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).



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Computing and communications technologies are having a truly disruptive effect on societies and business worldwide. Mobile payments, wireless communications and the ‘Internet of Things’ are transforming the way we approach key challenges in development, security, healthcare and the environment. Read more

Computing and communications technologies are having a truly disruptive effect on societies and business worldwide. Mobile payments, wireless communications and the ‘Internet of Things’ are transforming the way we approach key challenges in development, security, healthcare and the environment.

Taught jointly by the School of Computing and the School of Electronic and Electrical Engineering, this course will give you a grasp of all layers needed for mobile communication and computation, from the physical network layer through to the applications that run on mobile devices.

You’ll gain a full understanding of the web and cloud computing infrastructure, as core modules give you a foundation in key topics like systems programming and data communications. A range of optional modules will then allow you to focus on topics that suit your interests and career plans, from cloud computing to embedded systems design and high speed web architecture.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

You’ll take two core modules in Semester 1 that introduce you to fundamental topics like systems programming and network security. With this foundation, you’ll be able to gain high-level specialist knowledge through your choice of optional modules taught by the School of Computing and the School of Electronic and Electrical Engineering.

The optional modules you choose will enable you to direct your studies towards topics that suit your personal interests and career ambitions such as mobile app development, digital media engineering, big data, cloud computing and embedded systems design, among others.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Course structure

Compulsory modules

  • MSc Project 60 credits
  • Data Communications and Network Security 15 credits

Optional modules

  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Functional Programming 10 credits
  • Big Data Systems 15 credits
  • Mobile Applications Development 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Cloud Computing 15 credits
  • Graph Theory: Structure and Algorithms 15 credits
  • Communication Network Design 15 credits
  • Optical Communications Networks 15 credits
  • High Speed Internet Architecture 15 credits
  • Digital Media Engineering 15 credits

For more information on typical modules, read Mobile Computing and Communication Networks MSc in the course catalogue

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.Most projects are experimentally based and linked with companies within the oil and gas industry to ensure the topic of research is relevant to the field whilst also addressing a real-world problem.

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Career opportunities are extremely broad, covering jobs in the design of embedded software running on multi-core devices through to jobs involving the design and implementation of new mobile-applications centric systems for business. In the application of mobile computing skills, job opportunities span every area, from the automotive sector through to retail and banking.

You could launch a career in fields such as mobile app development, mobile systems architecture, project management, network consultancy. You could also work as an engineer in embedded mobile communications, network security or research and development among many others – and you’ll even be well-prepared for PhD study.

Careers support

You’ll have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations book appointments with qualified careers consultants and take part in employability workshops. Our annual Engineering and Computing Careers Fairs provide further opportunities to explore your career options with some of the UK’s leading employers.

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



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Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans. Read more
Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.
The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.
On the one hand, the Master’s in Computation in Neural and Artificial Systems addresses how models based on neural information processing can be used to develop artificial systems, probing of human information processing in closed-loop online settings, as well as the development of new machine learning techniques to better understand human brain function.
On the other hand it addresses various ways of modelling and understanding cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics, complexity theory and optimal control theory to neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner. We also look at new groundbreaking areas in the field of AI, like brain computer interfacing and deep learning.

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

Why study Computation in Neural and Artificial Systems at Radboud University?
- 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.

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

- Master’s students are free to use the state-of-the-art facilities available on campus, like equipment for brain imaging as EEG, fMRI and MEG.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Brain Network and Neuronal Communication. This will take three instead of two years.

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

- 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 will be able to use these facilities for developing new experimental research techniques, as well as for developing new machine learning algorithms to analyse the brain data and integrate them with brain-computer interfacing systems.

Some examples of possible thesis subjects:
- Deep learning
Recent breakthroughs in AI have led to the development of artificial neural networks that achieve human level performance in object recognition. This has led companies like Google and Facebook to invest a lot of research in this technology. Within the AI department you can do research on this topic. This can range from developing deep neural networks to map and decode thoughts from human brain activity to the development of speech recognition systems or neural networks that can play arcade games.

- Brain Computer Interfacing
Brain computer interfaces are systems which decode a users mental state online in real-time for the purpose of communication or control. An effective BCI requires both neuro-scientific insight (which mental states should we decode?) and technical expertise (which measurement systems and decoding algorithms should be used?). A project could be to develop new mental tasks that induce stronger/easier to decode signals, such as using broadband stimuli. Another project could be to develop new decoding methods better able to tease a weak signal from the background noise, such as adaptive-beam forming. Results for both would assessed by performing empirical studies with target users in one of the EEG/MEG/fMRI labs available in the institute.

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: Google, Facebook, IBM, Philips and the Brain Foundation. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Computation in Neural and Artificial Systems could get:
- PhD researcher on bio-inspired computing
- PhD researcher on neural decoding
- PhD researcher on neural information processing
- Machine learning expert in a software company
- Company founder for brain-based computer games
- Hospital-based designer of assistive technology for patients
- Policy advisor on new developments in neurotechnology
- Software developer for analysis and online visual displays of brain activity

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, Sweden and the United States.

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

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In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. Read more
In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.
The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, Complexity Theory, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.
Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

See the website http://www.ru.nl/masters/mathematics/foundations

Admission requirements for international students

1. A completed Bachelor's degree in Mathematics or Computer Science
In order to get admission to this Master’s you will need a completed Bachelor's in mathematics or computer science that have a strong mathematical background and theoretical interests. We will select students based on their motivation and their background. Mathematical maturity is essential and basic knowledge of logic and discrete mathematics is expected.

2. A proficiency in English
In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:
- TOEFL score of ≥575 (paper based) or ≥90 (internet based)
- IELTS score of ≥6.5
- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

There is a serious shortage of well-trained information specialists. Often students are offered a job before they have actually finished their study. About 20% of our graduates choose to go on to do a PhD but most find jobs as systems builders, ICT specialists or ICT managers in the private sector or within government.

Our approach to this field

In this Master's specialisation, mathematicians working in areas pertinent to (theoretical) computer science, like algebra and logic, and theoretical computer scientists, working in areas as formal methods and theorem proving, have joined forces to establish a specialisation in the Mathematical Foundations of Computer Science. The programme is unique in the Netherlands and will be built on the excellence of both research institutes and the successful collaborations therein.

The emphasis of the Master's is on a combination of a genuine theoretical and up-to-date foundation in the pertinent mathematical subjects combined with an equally genuine and up-to-date training in key aspects of theoretical computer science. For this reason, the mathematics courses in this curriculum concentrate on Algebra, General Topology, Logic, Number Theory, and Combinatorics. The computer science courses concentrate on Formal Methods, Type Theory, Category Theory, Coalgebra and Theorem Proving.

Our research in this field

Within both institutes, ICIS and WINST, there is a concentration of researchers working on mathematical logic and theoretical computer science with a collaboration that is unique in the Netherlands. The research topics range from work on algebra, logic and computability, to models of distributed, parallel and quantum computation, as well as mathematical abstractions to reason about programmes and programming languages.

See the website http://www.ru.nl/masters/mathematics/foundations

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In the last decade, urban informatics has gained recognition as a new approach to the study of cities and urban life. This is partly due to the harnessing of big and open data relating to urban infrastructure, socio-economic profiles and activities that take place in cities; and in part a result of developments in urban science, computational social science and complexity theory.

This course will enable you to understand and promote the theory and science of smart cities and to analyse city-scale data. You’ll also gain the skills to transform this data into knowledge, capitalising on emerging developments in big data and interdisciplinary methods to tackle the world’s urban challenges. Unlike most existing courses that have a disciplinary focus, this course offers a uniquely interdisciplinary approach to urban studies that combines training in theoretical approaches with knowledge of practice-based methodological skills. This means you’ll develop the skills to understand, support, and manage urban systems, and harness the opportunities that sensor, mobile and internet technologies offer within smart cities.

This course, a collaboration between the Centre for Interdisciplinary methodologies (CIM) and the Warwick Institute for the Science of Cities (WISC), also provides a pathway to the PhD programme in Urban Science at WISC, if you intend to undertake further postgraduate research at doctoral level. WISC has ties with CUSP (Center for the Urban Science and Progress) at New York University and the recently established CUSP London.

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