MSc
1 year full time, 2 years part time
Starts September 2017

Advanced Computer Science

Work with tomorrow’s computer systems – you’ll benefit from the expertise in the Department of Informatics and our practical links in the field of software engineering.

Advances across platforms, networks and computers mean new challenges, dwarfing the problems computer science has solved up to now. In order to meet these challenges, computing needs skilled scientists to be involved in system design.

“The tutors are excellent teachers – they have helped me to grasp key concepts and keep up-to-date with technology.” Jing Zhao
Advanced Computer Science MSc

Key facts

  • We were ranked as one of the top UK universities for research in computing in the 2014 Research Excellence Framework (REF): all aspects of our research environment were classified as either world leading or internationally excellent.
  • Our courses are designed for those who want to develop a career in the IT industry, research or academia.
  • You’ll work in an intellectually stimulating environment with research ranging from computer science to digital media to e-business.

How will I study?

In the autumn and spring terms, you’ll study core modules and options. In the summer term, you’ll work on a supervised dissertation. This may be research or commercially driven, with a significant practical element.

Assessment is through:

  • coursework and essays
  • unseen examinations
  • programming projects
  • a 12,000-word dissertation.

MSc project

You’ll complete a substantial MSc project, which is often practical as well as theoretical. The project exposes you to issues of:

  • project management
  • resourcing
  • planning and scheduling
  • documentation and communication
  • critical awareness and creative thinking.

You are encouraged to seek a project with a commercial or industrial flavour. Finding an industrial sponsor or host is fine, though you will still need an academic supervisor.

Full-time and part-time study

You can choose to study this course full time or part time. Find the modules for the full-time course below. 

Part-time courses will have their modules split evenly between the autumn and spring terms over two years, with the summers for dissertation work.

For details about the part-time course structure, contact us at enquiries@enginf.sussex.ac.uk

What will I study?

  • Module list

    Core modules

    Core modules are taken by all students on the course. They give you a solid grounding in your chosen subject and prepare you to explore the topics that interest you most.

    • Advanced Software Engineering

      15 credits
      Autumn Teaching, Year 1

      In this module, you study modern approaches to large-scale software production.

      You start by reviewing the key concepts in the whole life-cycle of a software product, such as:

      • requirement analysis
      • software architecture and design
      • implementation
      • quality assurance
      • maintenance activities.

      Following this review, you investigate modern software engineering technology, such as:

      • version control
      • build automation
      • testing
      • logical approaches to specification
      • verification of programs and domain-specific languages.

      As part of this module, you undertake team-based coursework, which involves the production of a significant software system.

    • 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.

    • Advanced Computer Science Project

      60 credits
      Spring Teaching, Year 1

      The dissertation will describe work undertaken as an individual project, supervised by a member of faculty. This project should add depth to an area studied elsewhere in the degree, or of personal interest. This may focus on computer science or software engineering, but should position itself with respect to the literature in the area of study and demonstrate the ability to apply relevant methods to solve a research problem and examine the properties of the solution. The poster presentation will give an opportunity for early feedback and give experience of presenting and defending research ideas, which will be valuable training for both academic and industrial settings. There is an expectation that a working computer program will be developed within the process, but it may be that a theoretical study, or experimental study through deployment or simulation will form a substantial part of the work - and emphasis in writing and assessment should reflect appropriate methods for the problem being studied. It is possible to reproduce prior results, in which case criticism of the original work, any extensions or variations and the detail available for reproduction should be the focus.

    • 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.

    Options

    Alongside your core modules, you can choose options to broaden your horizons and tailor your course to your interests.

    • Cryptography

      15 credits
      Autumn 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

      The module provides a theoretical and technical understanding of the major issues for existing large-scale E-Business and E-Commerce systems. Theoretical aspects include alternative E-Business strategies, marketing, branding, customer relationship issues and commercial website management. The technical part 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. Critical analysis of current and emerging technologies for E-Business and E-Commerce is carried out during seminars.

    • Human-Computer Interaction

      15 credits
      Autumn Teaching, Year 1

      Human–computer interaction (HCI) is concerned with designing, evaluating and deploying usable, effective and enjoyable technologies in a range of contexts. The aim of this module is to give an introduction to the key areas, approaches and developments in the field. Topics include:

      • principles of design
      • methods for evaluating interfaces with or without user involvement
      • techniques for prototyping and implementing graphical user interfaces.

      Ultimately you will be reflective practitioners, able to understand the 'tools' that you have in your user-centred design toolkit and to think constructively and analytically about the best uses, limitations and implications of using these tools to design and evaluate interactive technologies.

    • Web Computing

      15 credits
      Autumn Teaching, Year 1

      In this module, you are introduced to the models and technologies used to provide Web Services (over the Internet) - in particular XML technologies.

      You cover topics including:

      • XML
      • DTD
      • CSS
      • XML Schema
      • XML Transformation
      • servlets and Java APIs for parsing
      • processing documents.

      The main aim of this module is to introduce you to the prevailing technologies underlying the emergence of the Web Service as a major computation model over the Internet.

    • 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 you to advanced topics in digital communications, and to 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.
    • Image Processing

      15 credits
      Spring Teaching, Year 1

      You will cover topics including:
      • introduction to machine vision and relation to image processing
      • camera technologies, lenses for machine vision, image formation and resolution, display technologies
      • image acquisition hardware
      • histogram manipulations
      • linear invariant systems in two dimensions
      • the convolution operation and its discrete implementation as mask operators
      • first and second order differential edge detection operators, edge-filling techniques, Hough transform
      • the 2D Fourier transform and frequency domain filters, 2D correlation 
      • scene segmentation methods and region filling
      • pattern recognition techniques, shape descriptors, Fourier descriptors, template matching
      • examples of machine vision systems in industry.
    • Machine Learning

      15 credits
      Spring Teaching, Year 1

      In this module, you explore advanced techniques in machine learning.

      You use a systematic treatment, based on the following three key ingredients:

      • tasks
      • models
      • features.

      As part of the module, you are introduced to both regression and classification, and your studies emphasise concepts such as model performance, learnability and computational complexity.

      You learn techniques including:

      • probabilistic and non-probabilistic classification and regression methods
      • reinforcement learning approaches including the non-linear variants using kernel methods.

      You are also introduced to techniques for pre-processing the data (including PCA).

      You will then need to be able to implement, develop and deploy these techniques to real-world problems.

      In order to take this module, you need to have already taken the 'Mathematics & Computational Methods for Complex Systems' module (817G5), or have taken an equivalent mathematical module or have equivalent prior experience.

    • Mobile 3D Applications

      15 credits
      Spring Teaching, Year 1

      Through laboratory-based tuition and utilising Study Direct-based online teaching and learning materials (including slides, video, audio, demonstrations), this module will explore how 3D can be integrated into mobile web-based applications.

      Technologies covered include but are not limited to:

      • 3D modelling methods for real-time rendering and associated authoring packages (e.g. 3ds Max)
      • implementation of efficient navigation and interaction methods
      • responsive web design applied to the implementation of mobile web-based 3D applications.

      The main focus of this module is to gain practical experience on 3D modelling and programming (e.g. 3ds Max, X3D/VRML, X3DOM, HTML, CSS3, XML, JavaScript (and associated frameworks and libraries), AJAX, JSON, PHP and SQLite) to build a web mobile 3D application (an interactive 3D application that will render across desktop, tablet and mobile devices based on an MVC design pattern).

      Example web mobile 3D applications may include: a virtual museum, product configurator, vehicle visualisation, burglary simulation, or a simple web game.

    • 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
      • multimedia applications.
    • 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. There is 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
      • computer-supported collaborative learning.

Entry requirements

An upper second-class (2.1) undergraduate honours degree or above. Applicants with an undergraduate degree in computing, science, mathematics or engineering and significant computing experience are ideally suited to this course. Mature applicants with relevant experience will also be considered.

English language requirements

Standard level (IELTS 6.5, with not less than 6.0 in each section)

Find out about other English language qualifications we accept.

English language support

Don’t have the English language level for your course? Find out more about our pre-sessional courses.

Additional information for international students

We welcome applications from all over the world. Find out about international qualifications suitable for our Masters courses.

Visas and immigration

Find out how to apply for a student visa


Fees and scholarships

How much does it cost?

Fees

Home: £9,250 per year

EU: £9,250 per year

Channel Islands and Isle of Man: £9,250 per year

Overseas: £18,750 per year

Note that your fees may be subject to an increase on an annual basis.

How can I fund my course?

Postgraduate Masters loans

Borrow up to £10,280 to contribute to your postgraduate study.

Find out more about Postgraduate Masters Loans

Scholarships

Our aim is to ensure that every student who wants to study with us is able to despite financial barriers, so that we continue to attract talented and unique individuals.

Chancellor's Masters Scholarship (2017)

Open to students with a 1st class from a UK university or excellent grades from an EU university and offered a F/T place on a Sussex Masters in 2017

Application deadline:

1 August 2017

Find out more about the Chancellor's Masters Scholarship

Jan Metzger Scholarship for MSc in Intelligent and Adaptive Systems (2017)

£6,000 fee waiver for the MSc in Intelligent and Adaptive Systems.

Application deadline:

1 August 2017

Find out more about the Jan Metzger Scholarship for MSc in Intelligent and Adaptive Systems

Sussex Graduate Scholarship (2017)

Open to Sussex students who graduate with a first or upper second-class degree and offered a full-time place on a Sussex Masters course in 2017

Application deadline:

1 August 2017

Find out more about the Sussex Graduate Scholarship

Sussex India Scholarships (2017)

Sussex India Scholarships are worth £3,500 and are for overseas fee paying students from India commencing Masters study in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex India Scholarships

Sussex Malaysia Scholarships (2017)

Sussex Malaysia Scholarships are worth £3,500 and are for overseas fee paying students from Malaysia commencing Masters study in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex Malaysia Scholarships

Sussex Nigeria Scholarships (2017)

Sussex Nigeria Scholarships are worth £3,500 or £5,000 and are for overseas fee paying students from Nigeria commencing a Masters in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex Nigeria Scholarships

Sussex Pakistan Scholarships (2017)

Sussex Pakistan Scholarships are worth £3,500 and are for overseas fee paying students from Pakistan commencing Masters study in September 2017.

Application deadline:

1 August 2017

Find out more about the Sussex Pakistan Scholarships

How Masters scholarships make studying more affordable

Living costs

Find out typical living costs for studying at Sussex.


Faculty

Research in the Department of Informatics is split into four groups. 

  • Cognitive Language Processing Systems

    The research of this group addresses the science and engineering of complex systems for cognitively demanding, and data- and language-intensive domains, including the integration of methods from cognitive science, natural language engineering and machine learning.

    Prof John Carroll
    Professor of Computational Linguistics
    J.A.Carroll@sussex.ac.uk

    Research interests: Computational Linguistics, Computational/Corpus Linguistics, Machine Learning (AI), Medical Informatics, Natural Language Processing

    View profile

    Prof Peter Cheng
    Professor of Cognitive Sciences
    P.C.H.Cheng@sussex.ac.uk

    Research interests: Cognitive Science, Human computer interaction, Knowledge visualisation / information visualisation / visual analystics, Tactile graphics - cognitive science of, User-authentication - cognitive biometric

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    Dr Bill Keller
    Senior Lecturer in Artificial Intelligence
    billk@sussex.ac.uk

    Research interests: Computational Linguistics, Computational/Corpus Linguistics, Linguistics, Machine Learning (AI), Natural Language Processing, Probabilistic Methods, Semantics And Pragmatics

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    Dr Novi Quadrianto
    Senior Lecturer in Machine Learning
    N.Quadrianto@sussex.ac.uk

    Research interests: Bayesian Methods, Computer Vision - Machine Learning, Ethical Machine Learning, Kernel Methods, Machine Learning (AI), Optimisation (AI), Probabilistic Methods, Time Series

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    Prof David Weir
    Professor Of Computer Science
    D.J.Weir@sussex.ac.uk

    Research interests: Computational Linguistics, Data Science, Natural Language Processing

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    Dr Sharon Wood
    Senior Lecturer in Computer Science & Artificial Intelligence
    S.Wood@sussex.ac.uk

    Research interests: Artificial Intelligence, Cognitive Modelling, Cognitive Science

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  • 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.

    Dr Luc Berthouze
    Reader in Informatics
    L.Berthouze@sussex.ac.uk

    Research interests: Biomedical Signal Processing, Computational Neuroscience, Developmental Robotics, EEG, EMG, Motor Control, Network Theory and Complexity, Neuronal network, Nonlinear Dynamics and Chaos

    View profile

    Prof Maggie Boden
    Research Professor of Cognitive Science
    M.A.Boden@sussex.ac.uk

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    Dr Christopher Buckley
    Lecturer In Neural Computation
    C.L.Buckley@sussex.ac.uk

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    Dr Ron Chrisley
    Reader in Philosophy
    R.L.Chrisley@sussex.ac.uk

    Research interests: Artificial Intelligence, Cognition, Cognitive Science, Consciousness, Language & Philosophical Logic, Logic, Philosophy, Philosophy Of Mind, Philosophy of Science & Mathematics, & Mathematical Logic, Robotics

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    Prof Phil Husbands
    Research Professor Of Artificial Intelligence
    P.Husbands@sussex.ac.uk

    Research interests: Adaptive Systems, Artificial Intelligence, artificial life, Bio-inspired Neural Computing, Bio-inspired Robotics, Complex System Design, Computational Neuroscience, Digital Art & Design, Evolutionary Computation, evolutionary robotics, History of Science/Medicine/Technology, Machine Learning (AI), Mobile Robots, Nervous system, Optimisation Problems, Systems neuroscience

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    Prof Thomas Nowotny
    Professor Of Informatics
    T.Nowotny@sussex.ac.uk

    Research interests: Biomimetics, Chemical Sensing, Computational Neuroscience, Dynamic Clamp, Electronic Nose, GPU Computing, High Performance Computing, Insects, Ion channels, Machine Learning (AI), Neural networks, New Computing Paradigms, Olfaction, Robotics, Systems neuroscience

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    Dr Andy Philippides
    Reader in Informatics
    andrewop@sussex.ac.uk

    Research interests: computational biology, Computational Neuroscience, Computer Vision & Image Processing - Pattern Recognition, Evolutionary Computation, insect navigation, navigation, Robotics

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    Prof Anil Seth
    Professor of Cognitive & Computational Neuroscience
    A.K.Seth@sussex.ac.uk

    Research interests: Cognitive Neuroscience, Computational Neuroscience, Consciousness, EEG, Neuroimaging, neuropsychiatry, Neuropsychology, Psychology, Time Series, Virtual Reality

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    Dr Chris Thornton
    Lecturer in Computing Science
    C.Thornton@sussex.ac.uk

    Research interests: Information Theory, Predictive Processing, Theoretical Cognitive Science

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    Dr Sharon Wood
    Senior Lecturer in Computer Science & Artificial Intelligence
    S.Wood@sussex.ac.uk

    Research interests: Artificial Intelligence, Cognitive Modelling, Cognitive Science

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  • Foundations of Software Systems

    This group is interested in the theory and practice of future computation and communication. We:

    • build mathematical theories of computation
    • design and evaluate distributed applications and services
    • model and analyse data representing system configurations, social networks, trust and provenance.

    Dr Martin Berger
    Lecturer in Foundations Of Computation
    M.F.Berger@sussex.ac.uk

    Research interests: Automata Theory, Compiler Theory, Compilers, Computer Systems Security, Concurrency, Cryptography, Domain Specific Languages, Formal Methods, Formal Verification, Foundations of computation, Functional Programming, Just-In-Time Compilers, Logic, Logic for Computer Science, Meta-Programming, Network Security, Programming Languages, Programming Languages - Concurrent, Programming Languages - Distributed, Proof Assistants, Proof Theory, Semantics of Programming Languages, Software Engineering, Software Specification, Software Verification, Theorem Provers

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    Dr Ian Mackie
    Reader
    I.Mackie@sussex.ac.uk

    Research interests: Visual programming languages

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    Dr George Parisis
    Lecturer
    G.A.Parisis@sussex.ac.uk

    Research interests: Data Centre Networking and Storage, Information-Centric Networking, Network Management, Opportunistic, Delay-Tolerant Networking, Software-Defined Networking and Software Verification

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    Dr Bernhard Reus
    Senior Lecturer in Computer Science & Artificial Intelligence
    bernhard@sussex.ac.uk

    Research interests: Computational Complexity, Computer science, Foundations of computation, Software Verification

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    Dr Peter Schrammel
    Lecturer in Computer Science
    P.Schrammel@sussex.ac.uk

    Research interests: Abstract Interpretation, Abstraction, Embedded systems, Formal Verification, Hardware/Software Co-verification, Model Checking (Computing), Model-driven Software Eng, Real-time Software Systems, Satisfiability Modulo Theories, Software Engineering, Software Evolution, Software Quality, Software Safety, Software Security, Software Testing, Software Verification, Static Analysis

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    Prof Ian Wakeman
    Professor of Software Systems
    I.J.Wakeman@sussex.ac.uk

    Research interests: Communications networks, Datacenter Networking and Storage, delay tolerant networks, Distributed computing, Mobile Computing

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  • Interactive Systems

    This group is concerned with the interfaces between humans and digital technology. We investigate interaction in the broadest sense, and consider it in relation to both traditional desktop-based technology and also more recent digital technologies – including mobile, immersive, ubiquitous and pervasive computing.

    Dr Natalia Beloff
    Senior Lecturer in Software Engineering
    N.Beloff@sussex.ac.uk

    Research interests: Big Data Analytics, Business models for Digital innovation, E-Business Models, Internet of things, Medical Informatics, Numerical Analysis, Remote Sensing & Earth Observation

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    Dr Judith Good
    Reader in Informatics
    J.Good@sussex.ac.uk

    Research interests: Autism Spectrum Disorders, Game Based Learning, Game Creation for Learning, Learning, Learning Programming, Mobile Computing, Multimedia, Simulations for Learning, technology for autism

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    Dr Kate Howland
    Lecturer In Interaction Design
    K.L.Howland@sussex.ac.uk

    Research interests: End-user programming, Game Based Learning, Game Creation for Learning, Human computer interaction, Interaction design, Novice programming, Participatory Design, Technology Enhanced Learning

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    Prof Ann Light
    Professor of Design & Creative Technology
    Ann.Light@sussex.ac.uk

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    Dr Paul Newbury
    Senior Lecturer In Multimedia Systems
    P.Newbury@sussex.ac.uk

    Research interests: Technology Enhanced Learning, Virtual Prototyping

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    Dr Marianna Obrist
    Reader in Interaction Design
    M.Obrist@sussex.ac.uk

    Research interests: Interaction design

    View profile

    Dr Phil Watten
    Media Technology Manager
    P.L.Watten@sussex.ac.uk

    View profile

    Dr Martin White
    Reader in Computer Science
    M.White@sussex.ac.uk

    Research interests: 3D Reconstructions, Blockchain Applications, Digital Heritage, Healthy Living Applications

    View profile

Careers

Graduate destinations

92% of students from the School of Engineering and Informatics were in work or further study six months after graduating. Recent Informatics students have gone on to jobs including:

  • games lab manager, Ubisoft
  • front end developer, Brandwatch
  • UX designer, American Express.

(HESA EPI, Destinations of Post Graduate Leavers from Higher Education Survey 2015)

Your future career

Our students are highly employable, with 95% of recent graduates’ job roles being at professional or managerial level.

You'll leave the MSc equipped with the skills for a career in software and systems design, including roles requiring cutting-edge specialisation such as in mobile or cloud computing.

Employers of our graduates include:

  • Accenture
  • BMW
  • Google.

The MSc is also ideal preparation for research in academia or industry.

Working while you study

Our Careers and Employability Centre can help you find part-time work while you study. Find out more about career development and part-time work