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Masters Degrees (Complexity Science)

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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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Western science is dominated by ‘reductionism’ – the idea that natural phenomena can be Stephan Harding, Head of Holistic Science at Schumacher Collegefully explained in terms of their component parts. Read more
Western science is dominated by ‘reductionism’ – the idea that natural phenomena can be Stephan Harding, Head of Holistic Science at Schumacher Collegefully explained in terms of their component parts. Although it is a useful tool in certain circumstances, reductionism as a world view is incomplete and can be dangerous on its own since it suggests that by analysing the ‘mechanical’ workings of nature we can fully predict and manipulate it entirely for our own benefit.

Holistic Science integrates the useful aspects of reductionism and mainstream science by developing a more comprehensive basis for seeing and knowing. At the heart of this is Goethe’s rigorous and systematic way of involving the imagination in an appreciation of nature’s qualities, complexity and intrinsic value. Holistic thinking is stimulated by exercises using phenomenology and in tackling challenges related to physics, earth system science, ecology, evolutionary biology, organisational development and health studies. Since 1998, when the programme was pioneered at Schumacher College, it has developed a coherent methodology of holistic enquiry, providing a rigorous and ethical framework for a mature science.

The MSc takes you into a profound personal transformative learning journey helping you to join a growing group of international alumni contributing positively to ecological, economic and social change.

“Interactive, experiential and participatory learning encourages novel approaches to scientific investigation. Various non-traditional teaching formats, learning experiences and assessments are facilitated. Investigations are holistic in the sense that they are embodied as well as rational/intellectual and often result in different outcomes to traditional styles of research and reporting.”

- Philip Franses, Senior Lecturer of Holistic Science

Programme Overview

Develop an understanding of the pros and cons of using western science as a tool for gaining reliable knowledge about the world.
Learn how contemporary sustainability issues have come about and how we can successfully address them by combining rational and intuitive ways of knowing.
Gain an understanding of the importance of sensing, feeling and intuition for an expanded science.
Learn about a range of cutting edge alternative methodologies which integrate qualitative experience and quantitative measurement.
Develop an understanding of the emergent properties of whole systems through the lenses of chaos, complexity and Gaia theories, and discover how these approaches can help us deal with ecological, social and economic problems.
Understand how Holistic Science is being applied in the worlds of business, economics, health and mainstream science in the creation of a more sustainable world.
Develop a clear understanding of your own rational and emotional states and processes in the study of nature through experiential and reflective group enquiry.

Our Teachers and Guest Contributors Have Included:

Rupert Sheldrake
Patricia Shaw
Satish Kumar
Craig Holdrege
Mike Wride
Shantena Sabbadini
Jules Cashford
Bruce Lipton

Career Opportunities:

Our graduates from around the world have used their skills and knowledge for sustainable change to become eminent and important contributors to many fields, including climate change advocacy, education, scientific research, ecological design, healthcare, green business, protection of indigenous cultures, ecological restoration and sustainable agriculture. Working in in public, private and NGO sectors, many have set up their own projects or organisations.
What Past Participants Have Said:

“What I learnt and experienced from the MSc is that everything is ever changing. Working with the concepts of holistic science I experienced living with complexity and change as a way of life rather than as a stage I had to survive. For me, the gift of holistic science was to learn to appreciate the inherent potential in all situations. This has taught me to more effectively think, act and live with the tension of transitions through multidisciplinary approaches.”
- Anne Solgaard, Green Economy for UNEP/GRID-Arendal

“During my MSc in Holistic Science I learned a comprehensive qualitative approach to science that binds natural and cultural phenomena. It was a unique experience that transformed my own inner way of relating to complex circumstances and empowered me with the tools necessary to develop the way of life I’ve always dreamed of.“
- Sebastian Eslea Burch, founder of Gaia y Sofia

“The MSc certainly opened my eyes to new ways of doing business in a complex world. Both the formal teachings and the tremendous networking potential of the College have helped me in forging a professional life that I feel reflects my ideals.“
- Sophia Van Ruth, co-founder Urban Edibles

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A solid, theoretical understanding of computer technology with plenty of attention for the wide range of ICT applications. The enormous and rapidly growing power of ICT is the main driving force shaping our modern society. Read more
A solid, theoretical understanding of computer technology with plenty of attention for the wide range of ICT applications.

The enormous and rapidly growing power of ICT is the main driving force shaping our modern society. This goes beyond the technical and economical aspects. ICT is also essential in research as all sciences benefit from the raw power of software in processing huge quantities of data. But how do we manage and control the complexity of modern software? How can we make the most of the opportunities? And, not to be forgotten, how can we secure the ICT infrastructures we so heavily rely on? The Master’s programme in Computing Science covers all these aspects.

We offer specialisations in each terrain: security, software, data and the mathematics at the base of it all. These are not, however, isolated disciplines. We also look at the interesting interplay between them. For example, by taking privacy into account when dealing with big data. And by doing a thorough analysis of newly designed software to prevent security breaches later. Thanks to a large number of optional courses, you can decide where you want your focus to be.

The job opportunities in computer science are excellent: many of our students get offered jobs before they’ve even graduated and almost all have positions within six months after graduating. Many of our graduates find jobs as systems builders, ICT specialists or ICT managers and a few continue as researchers.

See the website http://www.ru.nl/masters/computingscience

Specialisations

- Cyber Security
You’ll learn to assess the security of existing ICT solutions, and how to develop more secure solutions for the future. This specialisation is offered in collaboration with the Eindhoven University of Technology, meaning you get taught by many of the best cyber security experts in the country.

- Data Science
You’ll learn how to turn real-world data sets into tools and useful insights, with the help of software and algorithms. Radboud University and the iCIS research institute are leading in research on legal and privacy aspects of data science and on the societal and administrative impact of data science.

- Mathematical Foundations of Computer Science
You’ll come to understand the fundamental mathematical concepts of computation and information in order to stretch the boundaries of computer technology. We’re the only specialisation in the country – and one of the few in the world – to focus on the theoretical and abstract playing field linking mathematics and computer science.

- Software Science
You’ll learn how to design high-level software that guarantees safety while controlling its complexity. At Radboud University, we are specialised in model based development. In other words, writing and testing code before they are unleashed in the real world or built into an expensive prototype.

- Societal Master's specialisations
You can either follow one of the above-mentioned research Master's specialisations as a whole (2 years), or you can combine the first year of the research specialisation with an additional year of one of the societal Master’s specialisations, namely:
- Science in Society
- Science, Management and Innovation

Why study Computing Science at Radboud University?

- All of our specialisations are closely related to the research carried out within the Institute for Computing and Information Science (iCIS).
- Our approach is pragmatic as well as theoretical. As an academic, we don’t just expect you to understand and make use of the appropriate tools, but also to program and develop your own.
- There are plenty of high profile companies in the vicinity such as Philips and ASML, where you could do an internship or the research for your Master’s project.
- Exceptional students who choose the Data Science specialisation have the opportunity to do a double degree in Computing Science together with the specialisation in Web and Language Interaction (Artificial Intelligence). This will take three instead of two years.

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 research in this field

The Institute for Computing and Information Science (iCIS) is the research institute that is connected to Radboud University. Within this institute there are three research sections:
- Model Based System Development
- Digital Security
- Intelligent Systems

Within each research section there are different departments/groups that have their own research. On the websites of the research sections you will find more information about their research, publications, the departments/groups and contact information.

See the website http://www.ru.nl/masters/computingscience

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This course will extend your prior knowledge and experience of computing and also prepare you for serious research, teaching and further graduate studies. Read more
This course will extend your prior knowledge and experience of computing and also prepare you for serious research, teaching and further graduate studies.

In addition to learning how to understand the fundamentals of computer architecture and organising, storing and retrieving data, you will learn how to identify software security problems in specialised client systems and to design effective countermeasures, based on the client requirements and priorities.

You will develop expertise in formal languages, the mathematical foundation of computability, and formal logic and systemic complexity, which may enhance your career prospects in a wide range of industry sectors, business and management.

Credit for previous study

Credits for recognised learning will be considered if you have successfully completed an honours or graduate diploma in this field of study.

Notes

This course is two years full-time for applicants with a bachelor degree in science or one year full-time for applicants with honours or a postgraduate diploma. You may choose to undertake intensive periods of course study or project work over the summer or vacation periods. To enrol in this course you will need to apply for the Master of Science – School of Science and Computing (308719) with a Computer Science major. You will graduate with a Master of Science (Computer Science).

2016 Curtin International Scholarships: Merit Scholarship

Curtin University is an inspiring, vibrant, international organisation, committed to making tomorrow better. It is a beacon for innovation, driving advances in technology through high-impact research and offering more than 100 practical, industry-aligned courses connecting to workplaces of tomorrow.

Ranked in the top two per cent of universities worldwide in the Academic Ranking of World Universities 2015, the University is also ranked 25th in the world for universities under the age of 50 in the QS World University Rankings 2015 Curtin also received an overall five-star excellence rating in the QS stars rating.

Curtin University strives to give high achieving international students the opportunity to gain an internationally recognised education through offering the Merit Scholarship. The Merit Scholarship will give you up to 25 per cent of your first year tuition fees and if you enrol in an ELB program at Curtin English before studying at Curtin, you will also receive a 10 per cent discount on your Curtin English fees.

For full details and terms and conditions of this scholarship, please visit: curtin.edu/int-scholarships and click on Merit.

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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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What do Facebook, the financial system, Internet or the brain have in common?. "Everything is connected, all is network". Read more
What do Facebook, the financial system, Internet or the brain have in common?

"Everything is connected, all is network"
From the underlying skeleton of social relations, the interdependent evolution of our financial system, to the emergent collective computation in the brain, most of the complex systems that appear in society, technology, and nature are ultimately characterised by a nontrivial pattern of inter-relations. This underlying architecture is in turn shaping how information diffuses and spreads, how resilient the system is against attacks or perturbations, or how complex patterns emerge at the systemic level from the aggregation of seemingly simple individuals.

Our MSc Network Science will provide a thorough grounding in the core principles of modelling and analysis of complex and networked systems, along with the principal analytical and numerical methodologies. This will open to students a host of career opportunities in systems and networks modelling industries, spanning the IT, financial, and biomedical sectors, that are now requiring such specialist knowledge and skills.

Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. Addressing the description and modelling of the architecture and dynamics of complex systems -systems composed by many interacting units that show collective behaviour- it stands as a new kind of science to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society.
Its impact and applications outside academia pervades technological sectors such as communications and infrastructures (Internet, transportation networks, energy networks, urban mobility), finance (financial risk and systemic instability, financial networks, interbank cross-correlations), marketing and IT (social media, data analytics), public health (epidemic spreading models), or biostatistics and network biology (brain modelling, protein interaction networks, postgenomic era), to cite a few. This specialist masters programme aims at providing graduate students and professionals with a rigorous training in the underlying mathematical concepts, the analysis and modelling of complex networks and networked systems, complemented with training in computing, numerical simulations and massive data analysis. It is aimed towards students with a mathematical background who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models.

Why study your MSc Network Science at Queen Mary?
This is a pioneering MSc in the UK, a joint programme, taught by our Schools of Mathematical Sciences, and Electronic Engineering and Computer Science, drawing on their strengths in research and teaching in the area of complex networks, mathematical modelling of complex systems, and data mining.

We teach what we know and what we do best. Within the School of Mathematics, the Complex Systems & Networks group is one of the biggest hubs in Network Science within the UK, where we address both fundamental and applied challenges in the mathematical modelling of complex systems with clear societal impact, in collaboration with several industrial stakeholders. Within the School of Electronic Engineering, the Networks group was founded in 1987, and has hugely expanded ever since, bringing their expertise in online social networks, data mining and cloud computing. The coalescence of both groups expertises has fostered the creation of this unique MSc.

More about our two schools

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research, teaching excellence and unrivalled links with business and the public sector. The School of Mathematical Sciences has a distinguished history on itself. We have been conducting pioneering mathematical research since the 1950s, and as one of the largest mathematical departments in the UK, with over 50 members of staff, the school can offer diverse postgraduate study opportunities across the field, from pure and applied mathematics, to finance and statistics. Along with the MSc in Network Science, our cohort of postgraduate students specialise in Mathematics and Statistics, Mathematical Finance and Financial Computing. We are one of the UK’s leading universities in the most recent national assessment of research quality, we were placed ninth in the UK (REF 2014) amongst multi-faculty universities. This means that the teaching on our postgraduate programmes is directly inspired by the world-leading research of our academics. Our staff includes international leaders in many areas of mathematical research, and the School is a hive of activity, providing a vibrant intellectual space for postgraduate study.

The School of Electronic Engineering and Computer Science is internationally recognised for their pioneering and ground-breaking research in several areas including machine learning and applied network analysis. This expertise uniquely complements the more theoretical knowledge offered by the School of Mathematical Sciences, providing a well balanced mix of theory and applications and offering a deep and robust programme that combines the foundations of the mathematics of networks with the latest cutting edge applications in real world problems.

Additionally, Queen Mary holds a university-level Bronze Award for the Athena SWAN Charter, which recognises and celebrates good employment practice for women working in mathematics, science, engineering and technology in higher education and research.

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Computer Science is one of the drivers of technological progress in all economic and social spheres. Those graduating with an M.Sc. Read more

About Computer Science

Computer Science is one of the drivers of technological progress in all economic and social spheres. Those graduating with an M.Sc. in Computer Science are specialists in at least one field of computer science who have wide-ranging science-based methodological expertise.
Graduates are able to define, autonomously and comprehensively, computer science problems and their applications, structure them and build abstract models. Moreover, they are able to define and implement solutions that are at the state of the art of technology and science.

Features

– A broad, international and relevant selection of courses
– As a student, you will work on cutting-edge research projects
– Individual guidance in small learning groups
– Excellent enterprise relations maintained by the chairs and institutes
– Numerous partnerships with universities throughout the world, including a double degree programme with the Institut national des sciences appliquées de Lyon (INSA)

Syllabus

The programme offers the following five focus modules:
1) Algorithms and Mathematical Modelling
2) Programming and Software Systems
3) Information and Communication Systems
4) Intelligent Technical Systems
5) IT Security and Reliability
1) Algorithms and Mathematical Modelling: This module teaches you about determinstic and stochastic algorithms, their implementation, evaluation and optimisation. You will acquire advanced knowledge of computer-based mathematical methods – particularly in the areas of algorithmic algebra and computational stochastics – as well as developing an in-depth expertise in mathematical modelling and complexity analysis of discrete and continuous problems.
2) Programming and Software Systems: This module imparts modern methods for constructing large-scale software systems, as well as creating and using software authoring, analysis and optimisation tools. In this module you will consolidate your knowledge of the various programming paradigms and languages, the structure of language processing systems, and learn to deal with parallelism in program procedures.
3) Information and Communication Systems: In this module you will study the interactions of the classic computer science areas of information systems and computer networks. This focus area represents an answer to the problem of increasing volume and complexity of worldwide information distribution and networks, and for the growing requirements on quality and performance of computer communication. Additionally, you will learn to transfer database results to multimedia data.
4) Intelligent Technical Systems: In this module you are acquainted with digital image and signal processing, embedded systems and applications of intelligent technical systems in industrial and assistance systems, which are necessary for production automation and process control, traffic control, medical and building technology. You will learn to develop complex applications using computer systems and deal with topics such as image reconstruction, camera calibration, sensor data fusion and optical measurement technology.
5) IT Security and Reliability: This module group is concerned with security and reliability of IT systems, e.g. in hardware circuitry and communication protocols, as well as complex, networked application systems. To ensure the secure operation of these systems you will learn design methodology, secure architectures and technical implementation of the underlying components.

Language requirements

Unless English is your native language or the language of your secondary or undergraduate education, you should provide an English language certificate at level B2 CEFR, e.g. TOEFL with a minimum score of 567 PBT, 87 iBT or ITP 543 (silver); IELTS starting from 5.5; or an equivalent language certificate.

To facilitate daily life in Germany, it would be beneficial for you to have German language skills at level A1 CEFR (beginner’s level). If you do not have any German skills when starting out on the programme, you will complete a compulsory beginner’s German course during your first year of study.

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Top archaeological researchers and heritage professionals use a raft of computational methods including GIS, data mining, web science, ABM, point-process modelling and network analysis. Read more
Top archaeological researchers and heritage professionals use a raft of computational methods including GIS, data mining, web science, ABM, point-process modelling and network analysis. To impress employers you need the flexibility to learn on the job, leverage open data and program open source software. This MSc draws on UCL's unparalleled concentration of expertise to equip you for future research or significantly enhance your employability.

Degree information

Students learn about a wide range of concepts that underpin computational approaches to archaeology and human history. Students become proficient in the archaeological application of both commercial and open source GIS software and learn other practical skills such as programming, data-mining, advanced spatial analysis with R, and agent-based simulation.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), two optional modules (30 credits) and a research dissertation (90 credits).

Core modules
-Archaeological Data Science
-Complexity, Space and Human History

Optional modules
-Agent-based Modelling of Human History
-Exploratory Data Analysis in Archaeology
-GIS Approaches to Past Landscapes
-GIS in Archaeology and History
-Remote Sensing
-Spatial Statistics, Network Analysis and Human History
-The Archaeology of Complex Urban Sites: Analytical and Interpretative Technology
-Web and Mobile GIS (by arrangement with the UCL Department of Civil and Geomatic Engineering
-Other options available within the UCL Institute of Archaeology

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

Teaching and learning
The programme is delivered through lectures, tutorials and practical sessions. Careful provision is made to facilitate remote access to software, tutorials, datasets and readings through a combination of dedicated websites and virtual learning environments. Assessment is through essays, practical components, project reports and portfolio, and the research dissertation.

Careers

Approximately one third of graduates of the programme have gone on to do PhDs at universities such as Cambridge, Leiden, McGill, Thessaloniki and Washington State. Of these, some continue to pursue GIS and/or spatial analysis techniques as a core research interest, while others use the skills and inferential rigour they acquired during their Master's as a platform for more wide-ranging doctoral research. Other graduates have gone to work in a range of archaeological and non-archaeological organisations worldwide. These include specialist careers in national governmental or heritage organisations, commercial archaeological units, planning departments, utility companies and consultancies.

Top career destinations for this degree:
-Database Administrator, Deloitte
-Data Science Analyst, M2M
-Graphical Information Systems (GIS) Technician, BSG Ecology

Employability
This degree offers a considerable range of transferable practical skills as well as instilling a more general inferential rigour which is attractive to almost any potential employer. Graduates will be comfortable with a wide range of web-based, database-led, statistical and cartographic tasks. They will be able to operate both commercial and oper source software, will be able to think clearly about both scientific and humanities-led issues, and will have a demonstrable track record of both individual research and group-based collaboration.

Why study this degree at UCL?

The teaching staff bring together a range and depth of expertise that enables students to develop specialisms including industry-standard and open-source GIS, advanced spatial and temporal statistics, computer simulation, geophysical prospection techniques and digital topographic survey.

Most practical classes are held in the institute's Archaeological Computing and GIS laboratory. This laboratory contains two Linux servers, ten powerful workstations running Microsoft Windows 7, a digitising table and map scanner.

Students benefit from the collaborations we have established with other institutions and GIS specialists in Canada, Germany, Italy and Greece together with several commercial archaeological units in the UK.

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Learning how to design high-level software that guarantees safety and correctness while still being in control of its complexity. Read more
Learning how to design high-level software that guarantees safety and correctness while still being in control of its complexity.

Software plays a role in almost every aspect of our daily lives and in every organisation anywhere in the world. It can often be a crucial key to their success. Well-structured software that is attuned to an organisation’s needs and future plans can be cost effective, improve efficiency, offer better services and be innovative. Many companies, in every branch out there, are therefore looking for highly skilled software specialists. Graduates of the Master’s specialisation in Software Science will have no trouble finding a job.

Producing software is not merely a technological enterprise but a deeply scientific and creative one as well. Modern cars drive on 20 million lines of code. How do we develop all this software and control its complexity? How do we ensure correctness of software on which the lives in a speeding car literally depend on? This specialisation goes far beyond basic code writing. It’s about analysing and testing code in order to improve it as well as simplify it.

Why study Software Science at Radboud University?

- Although not the only focus, our programme puts a lot of emphasis on embedded software and functional programming.
- We teach a unique range of software analysis techniques and application down to practical/commercial use in industry.
- This specialisation builds on the strong international reputation of the Institute for Computing and Information Sciences (iCIS) in areas such as model based and virtual product development, advanced programming, and domain specific languages. We also closely collaborate with the Embedded Systems Institute.
- Our approach is pragmatic as well as theoretical. As an academic, we don’t just expect you to understand and make use of the appropriate tools, but also to program and develop your own.
- For your Master’s research we have a large number of companies like Philips, ASML and NXP offering projects. There are always more projects than students.
- Thanks to free electives students can branch out to other Computing Science domain at Radboud University such as security, machine learning or more in-depth mathematical foundations of computer science.
- The job opportunities are excellent: some of our students get offered jobs before they’ve even graduated and almost all of our graduates have positions within six months after graduating.

See the website http://www.ru.nl/masters/softwarescience

Admission requirements for international students

1. A completed Bachelor's degree in Computing Science or related area
In order to get admission to this Master’s you will need a completed Bachelor’s degree in Computing Sciences or a related discipline.
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 >232 (computer 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

Writing good software is a highly creative process, which requires the ability to approach problems in entirely novel ways through computational thinking. Besides creativity, a professional software scientist also has fine problem-solving, analytical, programming, and communication skills. By combining software programming, model-checking techniques and human intellect, software scientists can make a real difference to help and improve the devices that govern such a large part of our lives.

The job perspective for our graduates is excellent. Industry desperately needs software science specialists at an academic level, and thus our graduates have no difficulty in find an interesting and challenging job. Several of our graduates decide to go for a PhD and stay at a university, but most of our students go for a career in industry. They then typically either find a job at a larger company as consultant or programmer, or they start up their own software company.

Examples of companies where our graduates end up include the big Dutch high-tech companies such as Océ, ASML, Vanderlande and Philips, ICT service providers such as Topicus and Info Support and companies started by Radboud graduates, like AIA and GX.

Our research in this field

The Master’s programme in Computing Sciences is offered in close collaboration with the research Institute for Computing and Information Sciences (iCIS). Research at iCIS is organised in three different research sections:
- Model Based System Development
- Digital Security
- Intelligent Systems

The Software Science specialisation builds on the strong international reputation of iCIS in areas such model based and virtual product development, advanced programming, and domain specific languages.

Research project and internship

For your research project, you may choose to do your internship at:
- A company
---- SME, such as as Océ, Vanderlande, Clarity or GX
---- multinational, such as the Philips, ASML, NXP, Logica or Reed Business Media
- A governmental institute, such as the (Dutch) Tax Authorities or the European Space Agency.
- Any department at Radboud University or another university with issues regarding software, like studying new techniques for loop bound analysis, the relation between classical logic and computational systems, or e-mail extension for iTasks.
- One of the iCIS departments, specialising on different aspects of Software Science.
- Abroad, under supervision of researchers from other universities that we collaborate with. For instance, exploring a new technique for automata learning at Uppsala University in Sweden, or verifying the correctness of Erlang refactoring transformations at the Eötvös Loránd University (ELTE) in Budapest, Hungary.

See the website http://www.ru.nl/masters/softwarescience

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IN BRIEF. Study a course that is unique in the UK and has been specifically developed to meet the skills gap. Course content can be applied to very diverse fields- there are many job opportunities in this area. Read more

IN BRIEF:

  • Study a course that is unique in the UK and has been specifically developed to meet the skills gap. Course content can be applied to very diverse fields- there are many job opportunities in this area.
  • Gain SAS certification.
  • Learn to tell a story from data. Become immersed in Big Data techniques and platforms, working with real-world messy data to gain experience across the data science stack.
  • Part-time study option
  • International students can apply

COURSE SUMMARY

Have you ever wanted to ‘Mung’ data? Apply Machine Learning techniques? Search for hidden patterns? Be part of Big Data?      

This course is your opportunity to specialize as a Data Scientist, one of the most in demand roles across all sectors including health, retail, and energy. Companies such as Google and Microsoft, and also public organisations such as the NHS are struggling to fill their vacancies in this field due to    a  lack of suitably qualified people. This course is unique in the UK in that it has been developed as a MSc conversion course – if you have a good honours degree in any discipline with a demonstrable mathematical aptitude, an enquiring mind, a practical and analytical approach to problem solving,    and  an ambition for a career in data science; then this course is for you.    

During your time with us, you will develop an awareness of the latest developments in the fields of Data Science and Big Data including advanced databases, data mining and big data tools such as Hadoop. You will also gain substantial knowledge and skills with the SAS business intelligence software suite  due  to    the  partnership of the University with the SAS Student Academy.  

"We are especially pleased to endorse the new MSc in Data Science. With the explosion of interest and investment in data science teams, our customers cannot get enough graduates with SAS-based analytical skills. Courses such as this new MSc are an important step forward by the University to addressing this skills shortage, especially amongst home students." - SAS

COURSE DETAILS

This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project worth 60 credits. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and could lead to ideas that you can develop for your MSc Project.

TEACHING

The course is focused around the underpinning knowledge and practical skills needed for employment within the data sciences industry. There will be 22 hours of lectures; 11 hours of tutorials and 22 hours workshops; 2 hours of examination-based assessment; and 245 hours of independent study, assessed coursework and preparation for examination. This makes a total of 300 hours total learning experience.

  • Lectures will be used to introduce ideas, and to stimulate group discussions.
  • Tutorials will be used to develop problem solving strategies and to provide practice and feedback with scenarios to help with exam preparation.
  • Workshops will be used to develop expertise in SAS tools, by analysing example datasets of increasing complexity.

ASSESSMENT

  • 50% of the assessment will comprise a practical project where students will be given some data, will devise and carry out an analysis strategy and will present their interpretations and explain their strategy. 
  • 50% will comprise an examination, which will assess more theoretical aspects of the course and will explore students’ immediate response to unseen scenarios or data.

CAREER PROSPECTS

A recent report by e-Skills and SAS (Big Data Analytics: An assessment of the demand for labour and skills, 2012-1017) indicates the demand forecast for staff with big data skills is predicted to ”rise by 92% between 2012 and 2017, and by 2017 there will be at least 28,000 job openings for big data staff in the UK each year…”

With this qualification, you’ll be equipped with the skill set and technical knowledge relevant for the data science and big data job market.

FURTHER STUDY

The Informatics Research Centre in the School of Computing, Science and Engineering at the University of Salford builds on the history, success and achievements of the research in Computer Science and Information Systems developed at the University of Salford over the last thirty years.

Evolving around Data and Information in all their types and usages, the Centre covers all phases and processes from data pre-processing to engineering and visualisation. The Centre is developing novel methods and systems for the analysis and recognition of various data sets, learning behaviours and causal models. The techniques and systems developed have a wide range of potential applications including digitisation of historical documents, medical diagnosis, semantic tagging, segmentation of types of viewers and their behaviours, text mining and retrieval and data visualisation.

Forensic computing, digital investigation and Cyber security is another area of expertise supported by the centre both at the theoretical and application levels.

Many students go on to further research in the fields of:

  • Actionable Knowledge Discovery and Semantic Web
  • Software Engineering and applications
  • Big Data, Data Mining and Analytics
  • Image and document processing and analysis
  • Cyber Security and Forensics
  • Information visualisation and virtual environments

FACILITIES

Facilities include a new Dell Cloud Computing platform with OpenStack and lab workstations, providing access to software platforms and languages specialized in Machine Learning, Data Mining, Statistical Analysis and Big Data including:

  • R, SAS Enterprise Guide & Miner, Python, Apache Hadoop & Spark, RapidMiner
  • NoSQL databases ie MongoDB


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Computer science drives the fundamental technologies of today’s connected world. Read more

Course Summary

Computer science drives the fundamental technologies of today’s connected world. Suited to candidates with significant programming experience, this umbrella programme covers the foundations of a range of specialisms as well as providing the opportunity to deepen your understanding of one or more of these areas through a range of optional modules.

Modules

Semester one: Computer Networks; Computer Vision; Designing Usable and Accessible Technologies; Evolution of Complexity; Foundations of Artificial Intelligence; Foundations of Cyber Security; Foundations of Data Science; Foundations of Web Science; Implementing Cyber Security; Intelligent Agents; Machine Learning; Robotic Systems; Software Engineering and Cyber Security; Software Modelling Tools and Techniques for Critical Systems; Software Project Management and Development; Topics in Computer Science; Web Development

Semester two: Advanced Computer Networks; Advanced Computer Vision; Advanced Databases; Advanced Intelligent Agents; Advanced Machine Learning; Automated Code Generation; Automated Software Verification; Biological Inspired Robotics; Biometrics; Computational Biology; Computational Finance; Cryptography; Data Mining; Data Visualisation; E-Business Strategy; Further Web Science; Game Design and Development; Image Processing; Open Data Innovation; Secure Systems; Semantic Web Technologies; Simulation Modelling for Computer Science; The Science of Online Social Networks

Plus three month independent research project culminating in a dissertation

Visit our website for further information...



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This MSc provides students with a thorough understanding of how science and scientifically based techniques can deliver immediate and sustainable reductions in crime. Read more
This MSc provides students with a thorough understanding of how science and scientifically based techniques can deliver immediate and sustainable reductions in crime. The programme focuses on how to better apply science to understand crime problems, develop strategies for preventing them, and increase the probability of detecting and arresting offenders.

Degree information

Students develop the ability to apply scientific principles to crime control, think more strategically in developing and implementing crime control policies, appreciate the complexity of implementation issues, critically assess the likely impact of planned crime reduction initiatives and generate more innovative proposals for reducing particular crime problems.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research dissertation (60 credits). A Postgraduate Diploma comprising four core modules (60 credits) and four optional modules (60 credits) is offered.

Core modules
-Foundations of Security and Crime Science
-Designing and Doing Research
-Preventing Crimes
-Quantitative Methods

Optional modules - students choose four of the following:
-Perspectives on Organised Crime
-Crime Mapping and Spatial Analysis
-Investigation and Detection
-Intelligence Gathering and Analysis
-Qualitative Methods
-Cybercrime
-Introduction to Cybersecurity

Dissertation/report
All students undertake an independent research project which culminates in a dissertation of approximately 10,000 words.

Teaching and learning
The programme is delivered through lectures, seminars, tutorials, projects, laboratory classes, and practical exercises. Practical work will involve the analysis and interpretation of data sets, and the development of new ideas for solving problems. Assessment is through lab and project reports, unseen written examination, coursework, presentations, and the dissertation.

Careers

Many graduates now work in the field of crime prevention and detection for public sector employers such as the Home Office, Police and Ministry of Defence, or private sector companies with a crime prevention and community safety focus. Other graduates go on to further doctoral research.

Top career destinations for this degree:
-Supply Chain Analyst, Sainsbury's
-MSc Forensic Psychology, University of Portsmouth
-Security Co-Ordinator, Murphy
-Forensic Associate, Deloitte
-Detective Constable, Metropolitan Police Service

Employability
Each year we ask our graduates to tell us about their experience of the programme and their career after leaving UCL and we include some real-life graduate profiles on our website: http://www.ucl.ac.uk/scs/degree-programmes/postgraduate/graduate-profiles

Why study this degree at UCL?

The UCL Security & Crime Science is a world-first, devoted specifically to reducing crime through teaching, research, public policy analysis and by the dissemination of evidence-based information on crime reduction.

The Crime Science MSc is a multidisciplinary degree, drawing on expertise in psychology, social science, statistics, mathematics, architecture, forensic sciences, design, geography and computing.

Our graduate students come from varied backgrounds; many are practitioners and are encouraged to contribute their experience in and out of the classroom.

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What's the Master of Computer Science about? . This Master will train you to become an expert in the development and up-front professional use of computer and software systems. Read more

What's the Master of Computer Science about? 

This Master will train you to become an expert in the development and up-front professional use of computer and software systems. Nowadays, these systems are indispensable in nearly all areas of our society: in industry, the public sector, health and many social applications for end users. They are also the most complex systems ever created by humans.

The programme will teach you to specify, design, implement, test and maintain advanced software systems. It will teach you how to handle complexity and how to deal with diverse requirements such as functionality, reliability, user friendliness, security, reliability, intelligence, efficiency and cost.

You will acquire all the necessary skills to tackle complex research questions, formulate your own research goals, and successfully achieve them.

You will be trained in communication skills and stimulated to acquire a broad societal view on the relevance of computer science and technology today.

Structure

The programme is structured around a mandatory core (42 credits) of which 18 credits are dependent on the Bachelor’s track followed by the incoming student. This core focuses heavily on software development, and is the main foundation of the programme.

You can choose between two advanced specialization areas: software security or artificial intelligence. In both specializations, you will conduct your own research and develop novel technology, guided by top-experts in the international research community.

The Master’s thesis covers 24 credits, and is started at the beginning of the second stage.

General education courses (12-14 credits) cover a wide variety of topics such as advanced language courses, economy, law, advanced mathematic courses. All students have the additional option to complete their programme with any course offered by the university (6 credits).

International

At the Faculty of Engineering Science, students are given the opportunity to complete one or two semesters of their degree within the Erasmus+ programme at a European university, or a university outside Europe. 

Students are also encouraged to carry out industrial and research internships abroad under supervision of the departmental Internship Coordinator. These internships take place between the third Bachelor’s year and the first Master’s year, or between the two Master’s years.

Other study abroad opportunities are short summer courses organised by the Board of European Students of Technology (BEST) network or by universities all over the world. 

The Faculty of Engineering Science is also member of the international networks CESAERCLUSTER and ATHENS, offering international opportunities as well.

More information on the international opportunities at the faculty is available on the website.

Strengths

The programme, courses, and areas of specialisation are strongly linked to the research groups. This guarantees a state-of-the-art education in the field of computer science. Research activities (e.g. Master’s thesis) also form part of a student’s curricula.

A significant number of courses are focused on industry-relevant skills and content. The amount of industry-related research projects in the department of computer science allows us to include relevant content in our courses.

The 2015 student survey indicated that the following aspects of our programme score very high: structure of the programme, electives, theoretical foundations, research & scientific content, quality of teaching staff, overall logistics.

This is an initial Master's programme and can be followed on a full-time or part-time basis.

Career perspectives

Software engineers can be found in nearly all sectors of society. Software is a crucial component in all industrial processes, in the service and entertainment industry, and in our society as a whole. Masters of Computer Science are active in the software-development industry as well as in telecommunication and other industries. Many of our graduates work in hospitals, in the banking sector, in social organisations, and for the government as heads of ICT.



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The increasing complexity of our society demands for specialists who can collect, manage, analyse and present spatial data using state-of-the-art methods and tools. Read more

MSc Geo-Information Science

The increasing complexity of our society demands for specialists who can collect, manage, analyse and present spatial data using state-of-the-art methods and tools. At Wageningen University we offer a unique, top-quality programme that blends geo-information science methods, technologies and applications within environmental and life sciences for a changing world. Our Geo-information Science graduates usually have a job waiting for them on graduation.

[[Programme summary]
Geo-information has become increasingly important to society as the number of environmental issues continue to rise: Geo-information provides the data we need to manage both the natural and social environment. It is indispensable for a broad range of domains like spatial planning, water management, nature conservation, environment management, agriculture, energy supply, disaster management and traffic and safety. The MSc GIS programme at Wageningen University offers you a blend of geo-information science methods, technologies and applications. The combined use of earth observation techniques (Remote Sensing) and Geographic Information Systems for problem-solving within the environmental and social disciplines is a unique feature of the Wageningen Approach. During your study, you take courses on the acquisition, storage, analysis and visualisation of spatial data. You learn to recognise, describe and analyse problems in relevant environmental application fields; this includes training in the development of prototypes. You also learn about the technical and organisational role of geo-information in institutes and companies: how to communicate well, keep abreast of GI scientific and technical developments, and how to apply these developments in specific fields. Depending on your background, research topics and previous education, you can also choose relevant courses in application domains or ICT.

Specialisations

The Geo-Information Science programme is an intensive programme offering students opportunities to specialise by taking advanced courses in GIS and/or Remote Sensing, and by selecting courses in a range of application fields or geo-information technology. Furthermore, you develop your GIS profile by completing a Master’s research thesis in one of the following research fields:
• sensing and measuring
• modelling and visualization
• integrated land monitoring
• human-space interactions
• empowering and engaging communities
Your choice of internship location is another factor in developing your profile and specialisation.

Your future career

Graduates in Geo-Information Science have excellent career prospects; most have job offers before they graduate. Many of our graduates work in research, either in PhD programmes or for research institutes all over the world; Wageningen UR, including Alterra, has the largest group of GI-scientists in the Netherlands. Many others are employed as technical specialists, consultants or project leaders for global companies like Royal Haskoning, Arcadis and Grontmij. And lastly, others work for local or central government agencies and NGOs, including environmental assessment programmes. Would you like to generate and use geo-information to solve global problems like flooding, planning, or the migration of wild animals? Or do you want to provide geo-information to the public or government? Then join the two-year Geo-information Science Master programme at Wageningen University. You have a Bachelor degree in the field of environmental sciences, geography and planning, landscape architecture, food and agricultural sciences, (geo)- information sciences or even social sciences.

Alumnus Frank Salet.
During his career, Frank worked within fields where the use of GIS is unique, challenging or still developing. After a few GIS positions at mostly commercial companies, he is now working at an NGO in Nigeria on the eradication of polio. For the project he has temporarily moved to Nigeria to set up the GIS work, together with a team of 20 Nigerian GIS specialists. He is now working in a multicultural environment just like during his master in Wageningen. Frank is very positive about the connection between the master and his professional career: “All courses within the master programme have formed the tools that I still use for each job I take on.”

Related programmes:
MSc Geographical Information Management and Applications
MSc Forest and Nature Conservation
MSc Landscape Architecture and Planning
MSc Environmental Sciences
MSc Biosystems Engineering.

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What do Facebook, the financial system, Internet or the brain have in common?. All are connected in a network. Read more
What do Facebook, the financial system, Internet or the brain have in common?

All are connected in a network. From the underlying skeleton of social relations, the interdependent evolution of our financial system, to the emergent collective computation in the brain, most of the complex systems that appear in society, technology, and nature are ultimately characterised by a nontrivial pattern of inter-relations. This underlying architecture is in turn shaping how information diffuses and spreads, how resilient the system is against attacks or perturbations, or how complex patterns emerge at the systemic level from the aggregation of seemingly simple individuals.

Our MSc in Network Science will provide a thorough grounding in the core principles of modelling and analysis of complex and networked systems, along with the principal analytical and numerical methodologies. This will open to students a host of career opportunities in systems and networks modelling industries, spanning the IT, financial, and biomedical sectors, that are now requiring such specialist knowledge and skills.

Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. Addressing the description and modelling of the architecture and dynamics of complex systems -systems composed by many interacting units that show collective behaviour- it stands as a new kind of science to cope with some of the most challenging endeavours we face today, in an ever increasingly more connected society.
Its impact and applications outside academia pervades technological sectors such as communications and infrastructures (Internet, transportation networks, energy networks, urban mobility), biostatistics and network biology (brain modelling, protein interaction networks, postgenomic era), public health (epidemic spreading models), marketing and IT (social media, data analytics) to cite a few. This specialist masters programme aims at providing graduate students and professionals with a rigorous training in the underlying mathematical concepts, the analysis and modelling of complex networks and networked systems, complemented with training in computing, numerical simulations and massive data analysis. It is aimed towards students whose undergraduate degree is in mathematics or a cognate discipline who wish to enter a career involving analysis and optimisation of diverse kinds of networks, networked dynamics and models.

Why study your MSc Network Science at Queen Mary?
This is a pioneering MSc in the UK, a joint programme, taught by our Schools of Mathematical Sciences, and Electronic Engineering and Computer Science, drawing on their strengths in research and teaching in the area of complex networks, mathematical modelling of complex systems, and data mining.

We teach what we know and what we do best. Within the School of Mathematics, the Complex Systems & Networks group is one of the biggest hubs in Network Science within the UK, where we address both fundamental and applied challenges in the mathematical modelling of complex systems with clear societal impact, in collaboration with several industrial stakeholders. Within the School of Electronic Engineering, the Networks group was founded in 1987, and has hugely expanded ever since, bringing their expertise in online social networks, data mining and cloud computing. The coalescence of both groups expertises has fostered the creation of this unique MSc.

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