Advanced Computer Science (2014 entry)

MSc, 1 year full time/2 years part time

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Computing at Sussex was ranked in the top 15 of UK universities for research in the 2008 Research Assessment Exercise (RAE). 95 per cent of our research was rated as internationally recognised or higher, with 70 per cent rated as internationally excellent or higher, and one-fifth rated as world leading. 

Computing at Sussex has excellent teaching and facilities and was ranked 21st in the UK in The Guardian University Guide 2014, 22nd in the UK in The Times Good University Guide 2013 and 30th in the UK in The Complete University Guide 2014. 

We have many successful business collaborations, enabling our taught courses to be informed by industry and facilitating exciting research. 

Our graduates are highly employable, with over 85 per cent entering employment in IT and related industries.  

Our portfolio of postgraduate degrees is designed to meet the needs of students who want to develop a career in the IT industry and those wishing to move into academia or a research career. 

We provide an intellectually stimulating environment with research in areas including pervasive computing technology, digital media and graphics, e-business, human-computer interaction, adaptive systems and artificial life, cognitive systems, natural language processing, and artistic and creative systems. 

Programme outline

This MSc equips you to work with tomorrow’s computer systems. Platforms may be mobile, embedded, distributed or multi-core, and require new techniques to make software efficient, correct and reliable. Networks may be wired or wireless, ad hoc or highly planned, high bandwidth or slow and unreliable – and overlaid with various applications and social connections. 

Computers are becoming aware of their surroundings: who is using them, where they are, what interfaces are available, how much energy they consume and the semantics of the data they process. Together these advances lead to challenges of a scale that dwarfs the problems computer science has solved up to now. 

In order to meet these challenges successfully, computing needs skilled scientists to be involved in system design. This course connects with research in the Department of Informatics, while retaining very practical links with software engineering and advanced networking issues, and offers options in areas including multimedia, web systems, security and business. 

Assessment 

You are assessed by coursework, unseen examinations, essays, programming projects, and a 12,000-word dissertation. 

We continue to develop and update our modules for 2014 entry to ensure you have the best student experience.In addition to the course structure below, you may find it helpful to refer to the 2012 modules tab.

Full-time course structure

Autumn term: Advanced Software Engineering • Topics in Computer Science. You also choose two options from Applied Natural Language Processing • Business and Project Management • E-Business and E-Commerce Systems • Human-Computer Interaction • Mathematics and Computational Methods for Complex Systems • Web Computing. 

Spring term: Limits of Computation • Pervasive Computing • Web Applications and Services. You also choose one option from Adaptive Systems • Advanced Digital Communication • Cryptography • Image Processing • Machine Learning • Multimedia Design and Applications • Technology-Enhanced Learning Environments • Web 3D Applications. 

Summer term: you undertake supervised work for the MSc dissertation. This may be research or commercially driven, but will usually require background research and a significant practical element, which may be focused on a software development, an experimental study or theoretical analysis. 

Computer science graduates who have substantial overlap between prior modules and those offered should enquire about an appropriate selection of options. 

Part-time course structure

The part-time structure for each degree is as follows: 

Year 1: in each of the autumn and spring terms you take two modules. In the summer term you undertake work on the dissertation. 

Year 2: you take two modules in the autumn term. In the spring and summer terms you complete work on the dissertation. 

Back to module list

Adaptive Systems

15 credits
Spring teaching, year 1

During this module you will gain familiarity with a number of different approaches to modelling and understanding adaptive processes in natural and artificial systems. This module covers recent work in AI that is geared towards understanding intelligence, both in natural and artificial systems, in terms of the generation of adaptive behaviour in autonomous agents acting in dynamic uncertain environments. Adaptation is studied at both the evolutionary and the lifetime scale.

Topics include: cybernetic roots of AI; frameworks for adaptive behaviour; evolutionary theory; genetic algorithms; somatic adaptation; classical control theory; fuzzy control; autonomous robots (behaviour based, subsumption architecture, evolutionary robotics); reinforcement learning; Q-learning; learning classifier systems; reinforcement learning in neural networks; applied reinforcement learning; and methods of analysis and modelling.

Advanced Digital Communications

15 credits
Spring teaching, year 1

The aim of the module is to introduce advanced topics in digital communications and provide you with up-to-date knowledge and skills required in the design and performance evaluation of wireless digital communication systems.

The following topics will be covered:

  • overview of digital communications
  • aims and constraints of the digital communication system designer
  • wireless communication fading channels
  • digital modulation
  • probability of error performance
  • bandwidth efficiency
  • adaptive modulation
  • error control coding
  • block coding
  • convolutional coding
  • interleaving
  • trellis coded modulation
  • spread spectrum
  • orthogonal frequency division multiplexing
  • multiuser communications
  • research project and simulation work using MATLAB software tools.

Advanced Software Engineering

15 credits
Autumn teaching, year 1

This course will revise project management skills, waterfall and agile models for software development, and UML. You will also be introduced to modern software development practices for use in the group project; software architectures, including component based, service based and aspect oriented software; development approaches for concurrency; and Domain Specific Languages

Applied Natural Language Processing

15 credits
Autumn teaching, year 1

Applied Natural Language Processing concerns the theory and practice of automatic text processing technologies. Topics covered on the module will include core, generic text processing models (e.g. , tokenisation, segmentation, stemming, lemmatisation, part-of-speech tagging, named entity recognition, phrasal chunking and dependency parsing) as well as problems and application areas (e.g. document classification, information retrieval and information extraction).

Hands-on experience with the practical aspects of this module will be gained through the weekly laboratory sessions will make extensive use of the Natural Language Toolkit which is a collection of natural language processing tools written in the Python programming language.

The seminars will provide in-depth discussion of a number of important issues that arise when developing natural language processing tools, including: experimentation and hypothesis testing; advanced data smoothing techniques; domain adaptation; topic modelling; active learning; generative versus discriminative learning; and semi-supervised learning.

Business and Project Management

15 credits
Autumn teaching, year 1

This module addresses wider business and project management issues that affect the technological and engineering environment. Some of these issues include: principles of strategic management, project management and planning, the business environment, auditing and control, organisational structure, business legislation, resource management, global markets and supply, and forecasting.

Cryptography

15 credits
Spring teaching, year 1

You will cover the following areas: 

  • Symmetric-key cryptosystems.
  • Hash functions and message authentication codes.
  • Public-key cryptosystems.
  • Complexity theory and one-way functions.
  • Primality and randomised algorithms.
  • Random number generation.
  • Elliptic curve cryptography.
  • Attacks on cryptosystems.
  • Quantum cryptography.
  • Cryptographic standards.

E-Business and E-Commerce Systems

15 credits
Autumn teaching, year 1

This module will give you a theoretical and technical understanding of the major issues for all large­-scale e­-business and e­-commerce systems. The theoretical component includes: alternative e-business strategies; marketing; branding; customer relationship issues; and commercial website management. The technical component covers the standard methods for large­-scale data storage, data movement, transformation, and application integration, together with the fundamentals of application architecture. Examples focus on the most recent developments in e­-business and e-commerce distributed systems. 

Human-Computer Interaction

15 credits
Autumn teaching, year 1

This module introduces you to some of the basic concepts and properties of topological spaces. The subject of topology has a central role in all of Mathematics and having a proper understanding of its concepts and main theorem is essential as part of the mathematics curriculum.

Topics that will be covered in this module include: topological spaces; separation axioms; metric spaces; convergence and completeness; compactness versus sequential compactness; total boundedness and E-nets; Arzela-Ascoli theorem; Tychonov theorem and applications.

Image Processing

15 credits
Spring teaching, year 1

 You will study: introduction to machine vision and relation to image processing; importance of scene constraints and methods of achieving these in the industrial environment; lighting techniques; ;radiometric and photometric units; camera technologies; lenses for machine vision; image formation and resolution; display technologies; image acquisition hardware and hardware implemented point operations; histogram manipulations; linear invariant systems theory in two dimensions; the convolution operation and its discrete implementation as mask operators; first and second differential edge detection operators; edge filling techniques; Hough transform; the 2-D Fourier transform and frequency domain filters; 2-D correlation. Scene segmentation methods and region filling; pattern recognition techniques: shape descriptors; Fourier descriptors; template matching; and examples of machine vision systems in industry.

Limits of Computation

15 credits
Spring teaching, year 1

This module is all about fundamental questions like 'what is computable?' and 'what is feasibly computable?'. The following topics are covered: what is a universal program? What is program specialisation? (partial evaluation, also known as s-m-n theorem). What is self-application? (boot-strapping). How can it be used to speed-up programs? How can an unsolvable problem be defined using WHILE? How can this be generalised? (Rice's theorem). Are there decidable but unfeasible problems? What are typical examples? What does feasible mean? How can one measure resource-usage of (time, space, non-determinism) of WHILE programs? What are asymptotic complexity classes and what are their limitations? What do we know about existence of optimal solutions?

Machine Learning

15 credits
Spring teaching, year 1

This module looks at data mining and machine learning. You will consider the main classes of problem and review the methods that are appropriate in each case.

Mathematics and Computational Methods for Complex Systems

15 credits
Autumn teaching, year 1

This module provides you with a foundation in mathematical and scientific computing techniques used widely in artificial intelligence, artificial life and related fields. The material covered in this module will give you the knowledge necessary to study a number of options on other MSc modules, and is a prerequisite for the Neural Networks and Computational Neuroscience modules. Coursework is based around Matlab packages.

Topics include: vectors and matrices; differential calculus; numerical integration; probability and hypothesis testing; dynamical systems theory.

Multimedia Design and Applications

15 credits
Spring teaching, year 1

You will examine how modern computing systems manage, deliver and present multimedia such as audio, video, and interactive grapics. Topics that you will study include: information coding, multimedia hardware, networked multimedia, ergonomics, interface design, and multimedia applications.

Pervasive Computing

15 credits
Spring teaching, year 1

This module provides you with an understanding of the issues, technologies and concepts underlying the vision of pervasive computing infrastructure, particularly in wireless networks, context-awareness, sensors and programming for limited and mobile devices. The module also provides you with experience of scientific and engineering techniques of design, experimentation, writing and critical review of literature. This is achieved through a combination of lectures on basic concepts and theory, seminars discussing literature and design, lab exercises in implementing systems with these technologies, and independent study building on this class work. Through examination of the various topics we will discuss appropriate experimental methods, including simulation and experimentation, and forms for the analysis of results.

Topics to be covered include: concepts in mobile and ad-hoc networks (including principles in wireless communications, addressing and routing in the mobile internet, identity and routing in ad-hoc networks and identity, routing and in-network processing in sensor networks); research and practise in context awareness ( including classification of context and uses of context; interfacing to sensors; resource discovery and system configuration, and location aware computing); design of pervasive computing systems (including programming with memory, CPU and power limitations for mobile devices and sensors; responding to context and resources, and mobile and pervasive user interfaces); and design and reporting of experiments (including research and engineering questions, and running experiments and reporting results).

Technology-Enhanced Learning Environments

15 credits
Spring teaching, year 1

This module emphasises learner-centred approaches to the design of educational and training systems. The module content will reflect current developments in learning theory, skill development, information representation and how individuals differ in terms of learning style. The module has a practical component, which will relate theories of learning and knowledge representation to design and evaluation. You will explore the history of educational systems, as well as issues relating to: intelligent tutoring systems; computer-based training; simulation and modelling environments; programming languages for learners; virtual reality in education and training; training agents; and computer-supported collaborative learning.

Topics in Computer Science

15 credits
Autumn teaching, year 1

An introduction to some key ideas in various areas in computer science, with particular reference to research in Informatics. Discussion of appropriate research methods will arise from this, including literature search, survey and prcis; use of proofs, simulation, experiments, user studies and discussion; presentation of results with appropriate statistical measures and analysis of variables, controls. Assessment will be via a literature review and research proposal which will discuss a relevant research question for the programme, a proposed approach for investigating it and the most suitable form for the answers to take - noting any comparison with prior work. The literature review and research proposal may form an input to your dissertation, but there is no obligation in this respect.
The module will start with some generic research methods and course guidance; and a diagnostic programming exercise to assess ability (and refer students who may benefit to additional programming help) and familiarise you with Sussex's systems.

Web 3D Applications

15 credits
Spring teaching, year 1

Through seminars, self directed e-learning and lab-based tuition, you will explore web 3D technologies including, but not limited to, 3D methods and tools, navigation and interaction, and web programming as applied to the implementation of web 3D applications.

This module will give you practical experience of web 3D modelling and programming, for example VRML/X3D, XHTML, and XML; building a web 3D environment, a small set of web pages with some 3D content; and creating an online application, such as a virtual museum, car simulation, 3D products, burglary simulation, or simple web game.

Web Applications and Services

15 credits
Spring teaching, year 1

This module provides an introduction to the models and technologies used to provide distributed applications and services over the Internet. You will study the features and problems of building distributed applications, such as naming, security, synchronisation, replication, object persistence and content distribution. You will use the framework provided by the Java Enterprise Edition to build distributed web applications.

Web Computing

15 credits
Autumn teaching, year 1

This module provides an introduction to the models and technologies used to provide Web Services (over the Internet), in particular XML technologies. Topics covered include: XML, DTD, CSS, XML Schema, XML Transformation, Servlets and Java APIs for parsing and processing documents.

The fundamental idea is to introduce you to the prevailing technologies underlying the emergence of the Web Service as a major computation model over the Internet.

Back to module list

Entry requirements

UK entrance requirements

A first- or upper second-class undergraduate honours degree. Applicants with an undergraduate degree in computing, science, mathematics or engineering with significant computing experience are ideally suited to this course. Mature applicants with relevant experience will also be considered on an individual basis.

Overseas entrance requirements

Overseas qualifications

If your country is not listed below, please contact the University at E pg.enquiries@sussex.ac.uk

CountryOverseas qualification
Australia Bachelor (Honours) degree with second-class upper division
Brazil Bacharel, Licenciado or professional title with a final mark of at least 8
Canada Bachelor degree with CGPA 3.3/4.0 (grade B+)
China Bachelor degree from a leading university with overall mark of 75%-85% depending on your university
Cyprus Bachelor degree or Ptychion with a final mark of at least 7.5
France Licence with mention bien or Maîtrise with final mark of at least 13
Germany Bachelor degree or Magister Artium with a final mark of 2.4 or better
Ghana Bachelor degree from a public university with second-class upper division
Greece Ptychion from an AEI with a final mark of at least 7.5
Hong Kong Bachelor (Honours) degree with second-class upper division
India Bachelor degree from a leading institution with overall mark of at least 60% or equivalent
Iran Bachelor degree (Licence or Karshenasi) with a final mark of at least 15
Italy Diploma di Laurea with an overall mark of at least 105
Japan Bachelor degree from a leading university with a minumum average of B+ or equivalent
Malaysia Bachelor degree with class 2 division 1
Mexico Licenciado with a final mark of at least 8
Nigeria Bachelor degree with second-class upper division or CGPA of at least 3.0/4.0
Pakistan Four-year bachelor degree, normally with a GPA of at least 3.3
Russia Magistr or Specialist Diploma with a minimum average mark of at least 4
South Africa Bachelor (Honours) degree or Bachelor degree in Technology with an overall mark of at least 70%
Saudi Arabia Bachelor degree with an overall mark of at least 70% or CGPA 3.5/5.0 or equivalent
South Korea Bachelor degree from a leading university with CGPA of at least 3.5/4.0 or equivalent
Spain Licenciado with a final mark of at least 2/4
Taiwan Bachelor degree with overall mark of 70%-85% depending on your university
Thailand Bachelor degree with CGPA of at least 3.0/4.0 or equivalent
Turkey Lisans Diplomasi with CGPA of at least 3.0/4.0 depending on your university
United Arab Emirates Bachelor degree with CGPA of at least 3.5/4.0 or equivalent
USA Bachelor degree with CGPA 3.3-3.5/4.0 depending on your university
Vietnam Masters degree with CGPA 3.5/4.0 or equivalent

If you have any questions about your qualifications after consulting our overseas qualifications, contact the University at E pg.enquiries@sussex.ac.uk

English language requirements

IELTS 6.5, with not less than 6.5 in Writing and 6.0 in the other sections. Internet TOEFL with 88 overall, with at least 20 in Listening, 20 in Reading, 22 in Speaking and 24 in Writing.

For more information, refer to English language requirements.

Visas and immigration

Find out more about Visas and immigration.

For more information about the admissions process at Sussex

For pre-application enquiries:

Student Recruitment Services
T +44 (0)1273 876787
E pg.enquiries@sussex.ac.uk

For post-application enquiries:

Postgraduate Admissions,
University of Sussex,
Sussex House, Falmer,
Brighton BN1 9RH, UK
T +44 (0)1273 877773
F +44 (0)1273 678545
E pg.applicants@sussex.ac.uk 

Fees and funding

Fees

Home UK/EU students: £5,5001
Channel Island and Isle of Man students: £5,5002
Overseas students: £16,2003

1 The fee shown is for the academic year 2013.
2 The fee shown is for the academic year 2013.
3 The fee shown is for the academic year 2013.

To find out about your fee status, living expenses and other costs, visit further financial information.

Funding

The funding sources listed below are for the subject area you are viewing and may not apply to all degrees listed within it. Please check the description of the individual funding source to make sure it is relevant to your chosen degree.

To find out more about funding and part-time work, visit further financial information.

Chancellor's International Scholarship (2014)

Region: International (Non UK/EU)
Level: PG (taught)
Application deadline: 1 May 2014

25 scholarships of a 50% tuition fee waiver

Fulbright-Sussex University Award (2014)

Region: International (Non UK/EU)
Level: PG (taught)
Application deadline: 15 October 2013

Each year, one award is offered to a US citizen for the first year of a postgraduate degree in any field at the University of Sussex.

Leverhulme Trade Charities Trust for Postgraduate Study (2014)

Region: UK
Level: PG (taught), PG (research)
Application deadline: 1 October 2013

The Leverhulme Trade Charities Trust are offering bursaries to Postgraduate students following any postgraduate degree courses in any subject.

Santander Scholarship (2014)

Region: International (Non UK/EU)
Level: PG (taught)
Application deadline: 1 May 2014

Two scholarships of £5000 fee waiver for students studying any postgraduate taught course.

USA Friends Scholarships (2014)

Region: International (Non UK/EU)
Level: PG (taught)
Application deadline: 3 April 2014

Two scholarships of an amount equivalent to $10,000 are available to nationals or residents of the USA on a one year taught Master's degree course.

Faculty interests

Research groups 

Research is a core activity of the Department of Informatics and is organised around our interdisciplinary research groups. Our research often entails collaborations between the groups, as well as with other academic schools at Sussex and external academic, institutional and commercial partners. The research groups are briefly described below, for more details, visit the Department of Informatics.

Cognitive and Language Processing Systems

The research of this group addresses the science and engineering of complex systems for cognitively demanding and language-intensive domains, including the application of methods from cognitive science and natural-language engineering. The group focuses on searching and classifying free text (eg medical records) in large quantities, cognitive processes of writing and drawing, cognitive modelling of processes such as attention and graphical production, and cognitively informed interactive tools for complex problem solving, decision making, instruction and learning. 

Faculty research interests include: 

Professor John Carroll Natural language parsing, acquiring knowledge about words from text, sentiment analysis, clinical text mining. 

Professor Peter Cheng The nature of representational systems (diagrams for complex problem solving, discovery and conceptual learning), processes of writing and drawing. 

Dr Bill Keller The use of language technology to support communication and interaction, language-aware technology, applications of distributional models of natural language semantics. 

Dr David Weir Controlling non-determinism in natural language generation, language in pervasive computing environments, efficient parsing, inferring knowledge about words from raw text. 

Dr Sharon Wood Multi-agent systems. Cognitive modelling, in particular information acquisition through cognitively plausible visual attention processes, and knowledge-based reasoning.  

Evolutionary and Adaptive Systems (EASy) 

The EASy group has been internationally prominent since it was established in the early 1990s. It is concerned with the interfaces between the biological and computational sciences, particularly with reference to furthering understanding of brains and minds. The group’s research is highly interdisciplinary and involves many strong links with other departments at Sussex. Research foci include adaptive and cognitive robotics, artificial life, bio-inspired computational methods, computational neuroscience, creative systems, history and philosophy of AI and ALife, clinical applications of neural modelling, machine learning, scientific studies of consciousness, and synthetic neuroethology. It runs the highly successful Centre for Computational Neuroscience and Robotics (CCNR) jointly with Sussex Neuroscience in the School of Life Sciences. Members of the group also direct the Centre for Research in Cognitive Science (COGS) and the Sackler Centre for Consciousness Science (SCCS), both important cross-campus initiatives. 

Faculty research interests include: 

Dr Luc Berthouze Motor development in infants and in machines, EEG-based brain-machine interfaces, epigenetic robotics, and modelling cognitive development with robotic systems. 

Professor Margaret Boden Computational approaches in the philosophy of mind and psychology, purpose and creativity, philosophy of AI and ALife, and social implications of AI. 

Dr Ron Chrisley Non-conceptual representation; philosophy of cognitive science, AI, mind, consciousness, computation; computer/robotic models of visual experience, emotion, creativity. 

Professor Phil Husbands Evolutionary and adaptive robotics, evolutionary computation, ALife, computational neuroscience, adaptive systems, neuromodulation, history of AI, creative systems. 

Dr Thomas Nowotny Information processing in nervous systems, sequence learning in neuronal systems, accurate conductance-based neuron models, and hybrid systems. 

Dr Andy Philippides Computational neuroscience and neuroethology, evolutionary robotics, insect visual homing strategies, and gaseous neuromodulators in neural networks. 

Professor Anil Seth Theoretical neuroscience and evolutionary and adaptive systems; time-series analysis of neural dynamics, neurorobotics; and evolutionary theory and ecological modelling. 

Dr Chris Thornton Computational learning using symbolic algorithms and connectionist mechanisms, and theories of creativity.  

Foundations of Software Systems

This group is interested in the theory and practice of future computation and communication. We build mathematical theories of computation and use such models to inform the design of programming languages and compilers. We design and evaluate distributed applications and services that provide the foundations of the pervasive computing infrastructure and other software systems. We model and analyse data representing system configurations, social networks, trust, and provenance. 

Faculty research interests include: 

Dr Martin Berger Concurrency theory, semantics and pragmatics of programming languages, program logics, metaprogramming, computer science methods in theoretical biology. 

Dr Dan Chalmers The design of pervasive computing systems, particularly those which process and consider emotion, social networks, trust and context to enable efficient and usable system behaviour. 

Dr Ian Mackie Foundations of programming languages and models of computation. Applying techniques from mathematical logic and quantum mechanics to programming language implementation. 

Dr Bernhard Reus Mathematical semantics of programming languages and their foundations; constructive logic; and techniques and tools supporting program analysis, design and verification. 

Dr Ian Wakeman Networks and distributed systems, emphasis on design from the user perspective, pervasive computing, computational trust. 

Interactive Systems

This research group operates at the intersection between people and digital technology. We are interested in interaction in the broadest sense and consider it in relation to both traditional desktop-based technologies and more novel digital technologies, including mobile, immersive, ubiquitous and pervasive technologies. 

We are interested in users of all kinds, ranging from experts using technology in their work (such as medical professionals) and experts developing technology for their work (such as programmers) to novices of all kinds (from children using educational technology through to adults using social technology). 

Our research focuses on human-computer interaction, accessibility, music informatics, learning with and through technology (including social networks), technology-enhanced social interaction, new models of e-business, e-government and e-citizenship, tangible and embodied interaction, motion capture techniques, building virtual worlds for digital heritage and other applications, real-time animation, digital content creation and digital video. 

Faculty research interests include: 

Dr Natalia Beloff New models of e-business, business models for small and medium digital enterprises, adver-gaming, advertising for social networks, education and social networks. 

Dr Judith Good Constructivist learning environments, game-based learning, technology toolkits for learning, visual programming languages, learner-centred and participatory design methodologies. 

Dr Paul Newbury Multimedia systems, in particular virtual prototyping, ubiquitous systems and digital content creation. Technology-enhanced learning and video techniques for distance learning. 

Dr Phil Watten Software development; virtual prototyping; high-level design; system modelling; display systems; interface design; and media production, new media and web broadcasting. 

Dr Martin White 3D graphics; virtual, augmented and mixed reality; animation; motion sensing; motion gaming; digital heritage systems; interaction; work flows. 

Interdisciplinary research centres 

The Department of Informatics plays a central role in the following major interdisciplinary research centres: 

Centre for Computational Neuroscience and Robotics (CCNR) 

CCNR is a collaboration between the Department of Informatics and the School of Life Sciences. This thriving centre seeks to explore and exploit the interfaces between the biological and computational sciences. CCNR is jointly run with the Evolutionary and Adaptive Systems group. 

Centre for Research in Cognitive Science (COGS) 

COGS is an internationally recognised centre for interdisciplinary investigation into the nature of cognition, be it natural or artificial. Staff in Informatics and Psychology, as well as Sussex linguists, focus on teaching and research. 

Sackler Centre for Consciousness Science (SCCS) 

SCCS is a venture between the Department of Informatics, the School of Psychology, and the Brighton and Sussex Medical School. The Centre’s aim is to unravel the complex neural mechanisms underlying conscious experience by bringing together computational modelling, cognitive neuroscience, and clinical applications. 

Careers and profiles

This course equips you with the skills for a career in software and systems design, including roles requiring cutting-edge specialisation such as in mobile computing or taking leadership in complex problem solving. It is also an ideal route into research in academia or industry. 

Jing's student perspective

Jing Zhao

‘I chose to do an MSc in Advanced Computer Science at Sussex because of the excellent links that the School of Engineering and Informatics has with industry and government, and the high quality of education on offer. As well as getting a good grounding in the fundamentals of advanced computing practice, I’ve  also focused on interesting research fields such as pervasive computing, multimedia and web applications.

‘The tutors at Sussex are at the forefront of their fields and have excellent teaching skills. Their patience and kindness has helped me to grasp key concepts in advanced computer science and to keep up to date with technology.

‘The facilities within the School of Engineering and Informatics are very student friendly with great support on offer, and computers available 24/7.

‘As an international student, for whom English is a second language, I was offered a pre-sessional English course, which has really helped me to adapt to study in the UK and has been invaluable for writing assignments and essays in appropriate academic language throughout my degree.

‘I’ve thoroughly enjoyed my experience at Sussex and after I graduate I hope to continue to work in the field of IT development.’

Jing Zhao
MSc in Advanced Computer Science

For more information, visit Careers and alumni.

School and contacts

School of Engineering and Informatics

The School of Engineering and Informatics brings together the areas of mechanical and electrical engineering with informatics, in particular computer science and artificial intelligence, and product design.

Department of Informatics

The Department of Informatics is an internationally renowned centre for teaching and research in computer science, and provides the skills and knowledge required for a future in this dynamic field. 

Informatics, Postgraduate Admissions,
University of Sussex, Falmer,
Brighton BN1 9QJ, UK
T +44 (0)1273 678195
F +44 (0)1273 877873
E informaticsoffice@sussex.ac.uk
Department of Informatics

Postgraduate Open Day 2013

4 December 2013, 1pm-4pm
Bramber House, University of Sussex

  • talk to academic faculty and current postgraduate students
  • subject talks and presentations on postgraduate study, research and funding
  • choose from our exciting range of taught Masters and research degrees
  • find out how postgraduate study can improve your career prospects
  • get details of our excellent funding schemes for taught postgraduate study.

To register your interest in attending, visit Postgraduate Open Day.

Can’t make it to our Postgraduate Open Day? You might be interested in attending one of our Discover Postgraduate Study information sessions.

Discover Postgraduate Study information sessions

If you can’t make it to our Postgraduate Open Day, you’re welcome to attend one of our Discover Postgraduate Study information sessions. These are held in the spring and summer terms and enable you to find out more about postgraduate study and the opportunities Sussex has to offer.

Visit Discover Postgraduate study to book your place.

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We run weekly guided campus tours every Wednesday afternoon, year round. Book a place online at Visit us and Open Days.

You are also welcome to visit the University independently without any pre-arrangement.

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