Computing, artificial intelligence and IT

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Computing, artificial

intelligence and IT

Essentials Taught courses

MSc in Advanced Computer Science MSc in Computing with Digital Media MSc in Evolutionary and Adaptive Systems MSc in Human-Computer Interaction MSc in Information Technology with Business and Management MSc in Intelligent Systems MSc in Management of Information Technology

Research courses

MPhil, PhD in Cognitive Science MPhil, PhD in Informatics Related courses

MSc in Computational Mathematics (p126) MSc in Digital Communication Systems (p89) MSc in Embedded Digital Systems (p89) Entry requirements

For information on overseas qualifications, refer to pages 168-170. Also refer to Additional entry information, listed with relevant course entries

MSc in Computing with Digital Media, MSc in Management of Information Technology A first or second-class undergraduate honours degree. Mature applicants with relevant experience will also be considered MSc in all other subjects

A first- or upper second-class undergraduate honours degree. Mature applicants with relevant experience will also be considered MPhil, PhD

A first- or upper second-class undergraduate honours degree in a subject relevant to your chosen area of research

English language requirements IELTS 6.5, with not less than 6.0 in each section. For more information and alternative English language requirements, refer to page 168

Pre-Masters for non-EU students If your qualifications (including English language) do not yet meet our entry requirements for admission directly to any of the MSc courses listed above (except the MSc in Advanced Computer Science and the MSc in Evolutionary and Adaptive Systems), we offer a Pre-Masters entry route. For more information, refer to page 36

Key facts

• Sussex is 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.

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

• Our students are highly employable, with 95 per cent of recent graduates’ job roles being at professional or managerial level. • Our portfolio of postgraduate courses 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 computer science and software systems, digital media, e-business, human-computer interaction, adaptive systems and artificial life, cognitive systems, natural language processing, and artistic and creative systems. Applications deadline

If you are a non-EEA or Swiss national student applying for a research degree, you must allow sufficient time for your University application to be considered and processed in time for you to apply for clearance from the UK Government’s Academic Technology Approval Scheme (ATAS) and a Tier 4 student visa (if appropriate)

Scholarships, fees and living costs Refer to pages 24 and 173-174, and visit www.sussex.ac.uk/study/money Contact us

Informatics, PG Admissions, University of Sussex, Falmer, Brighton BN1 9QJ, UK T +44 (0)1273 678195 E [email protected] www.sussex.ac.uk/informatics Open Days

Our Postgraduate Open Day will be held on 17 February 2016. The PhD Open Evening will be held on 25 November 2015. We also run regular campus tours. Call 01273 876787 or book online at www.sussex.ac.uk/visitors

Taught courses

MSc in Advanced Computer Science 1 year full time/2 years part time This MSc equips you to work with tomorrow’s computer systems. Platforms may be mobile, embedded, distributed, cloud-based 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.

Additional entry information

Applicants with a good undergraduate honours degree in computing, science, mathematics or engineering with significant computing experience are ideally suited to this course. Career paths

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 or cloud computing. Employers of our graduates include Accenture, BMW and Google. This MSc is also ideal preparation for research in academia or industry.

Course structure

Autumn term: Advanced Software Engineering • Topics in Computer Science. You also choose two options from Cryptography • E-Business and E-Commerce Systems • Human-Computer Interaction • Web Computing.

Spring term: Web Applications and Services. You also choose three options from Adaptive Systems • Advanced Digital Communication • 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 usually requires 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 alternative selection of options.

Assessment

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

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MSc in Human-Computer Interaction 1 year full time/2 years part time This course explores how to apply techniques from cognitive science, psychology and software engineering to the design, implementation and evaluation of computing systems from a human-centred perspective. This MSc encompasses user experience and interaction design. Additional entry information

Applicants should have an interest in computing systems from a human perspective and should have an undergraduate background in computing, or psychology, or a degree with substantial computing or social-science content. Career paths

Our graduates work for a diverse range of organisations from small companies to multinationals such as Kineo, Stream Media, HP, Eurotherm and American Express. Their roles include customer experience executive, senior application consultant, product development executive and principal software engineer. Others have set up web design, human factors consultancy and new media businesses. Some continue with doctoral study leading to research and academic careers.

Autumn term: Human-Computer Interaction • Object-Oriented Programming (students with a high level of programming experience may take Advanced Software Engineering) • Real-World Cognition. You also choose one option from Applied Natural Language Processing • E-Business and E-Commerce Systems. Spring term: HCI Advanced Topics

• Psychological Methods for System Evaluation • Technology-Enhanced Learning Environments. You also choose one option from Generative Creativity • Multimedia Design and Applications. Summer term: you undertake supervised work for the MSc dissertation, a project in which you either design and evaluate a human-centred computer system or investigate an aspect of interactivity.

Assessment

You are assessed by coursework, examinations, essays, programming projects, group projects, presentations and a 12,000-word dissertation. MSc in Computing with Digital Media

1 year full time/2 years part time Industries such as computer entertainment, television, film and video production are relying increasingly on computer-generated digital media and virtual content. It is now commonplace to use interactive digital media in anything from teaching environments to games and from websites to engineering design. This involves not only the creation of digital content but its implementation in an interactive environment and its distribution over the diverse kinds of networks available in today’s world. This MSc enables you to build web-based distributed multimedia applications, computer-generated animations and interactive virtual environments, emphasising the need to adopt a human-centred approach.

The course is supported by the Media Technology Laboratory, which provides state-of-the-art digital facilities, software development tools, multimedia content creation tools, studio facilities and professional video-editing systems. The Laboratory enables you to undertake practical work assignments using facilities that you would find in the modern digital media industry.

This course is for applicants intending to deepen their understanding of technical digital media. It is suited to those with a previous degree in computer science, mathematics or the natural sciences. Applicants with media degrees who can demonstrate practical computing knowledge will also be considered.

Career paths

Brighton is home to hundreds of digital media companies. Our graduates have gone on to pursue careers in web development, games programming, e-learning production and 3D modelling, and hold posts in digital media both in Brighton and further afield. This MSc is also an ideal entry point for PhD research in the field of digital media.

Autumn term: 3D Animation • 3D Modelling and Rendering • Human-Computer Interaction • Object-Oriented Programming (students with a high level of programming experience may take Advanced Software Engineering).

Spring term: Interactive 3D Programming • Multimedia Design and Applications • Web 3D Applications. You also choose one option from Generative Creativity • Live Video Production • Technology-Enhanced Learning Environments. Summer term: you undertake supervised work for the MSc dissertation, which should usually be based on a multimedia programming project. Assessment

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

MSc in Evolutionary and Adaptive Systems 1 year full time/2 years part time

The study of natural and artificial evolutionary and adaptive systems is at the heart of rapidly developing areas, ranging from artificial intelligence and autonomous robotics to neuroscience, consciousness and cognitive science.

Sussex is home to the Evolutionary and Adaptive Systems (EASy) research group which is renowned for its research in these interdisciplinary areas.

The course provides you with solid foundations in key areas such as adaptive systems, machine learning, biologically-inspired robotics, computational neuroscience, evolutionary computation and complex systems, as well as the opportunity to take a range of options in cutting-edge areas such as the science of consciousness. We also provide introductory courses in programming, enabling students from computing and non-computing backgrounds to access our specialist options.

This course was the first of its kind and remains the gold standard in its area. You will be taught by experts at the forefront of their fields and enjoy many opportunities to interact with a thriving community of active researchers.

Applicants typically have a background in a scientific or technical subject or other disciplines requiring either numeracy or computer literacy. Students from other backgrounds who can demonstrate numeracy or computer literacy will also be considered.

Career paths

This MSc will provide you with technical and research skills sought after across a range of careers. Many recent graduates have gone on to PhD study at Sussex and other prestigious universities and now work in academic or industrial research. Others have established careers in the software, entertainment and financial sectors, working for major companies such as DeepMind, Capgemini, IBM, Microsoft, NaturalMotion and Sega, as well as successfully setting up their own companies.

Autumn term: Artificial Life • Intelligence in Animals and Machines • Mathematics and Computational Methods for Complex Systems • Object-Oriented Programming (students with sufficient programming experience may take Intelligent Systems Techniques • Applied Natural Language Processing • Advanced Software Engineering)

Spring term: Adaptive Systems • Neural Networks. Also two options from Computational Neuroscience • Generative Creativity • Image Processing • Machine Learning • Neuroscience of Consciousness • Sensory and Motor Functions of the Nervous System. Summer term: you undertake a dissertation project under the supervision of a member of faculty, which is usually based on a programming project. This gives you the opportunity to develop further what you have learnt in the context of a piece of research. It is not unusual for work from dissertation projects to be published in conference proceedings or journals. Assessment

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

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Autumn term: Object-Oriented Programming (students with a high level of programming experience may take Advanced Software Engineering) • E-Business and E-Commerce Systems • Web Computing. You also choose one option from Business and Project Management • Change and Leadership • Human-Computer Interaction • Intelligent Systems Techniques • Management, Innovation and Organisational Performance.

Spring term: Web Applications and Services • Managing Complex Projects, Products and Systems. You also choose two options from Business in Context (Europe or Asia) • Critical Perspectives on Management, Organisations and Innovation • HCI Advanced Topics • ICT Policy and Strategy • Machine Learning • Multimedia Design and Applications • Strategic Management.

Summer term: you undertake supervised work for the MSc dissertation, which is based on a substantial research project.

Assessment

Taught modules are assessed by a variety of methods including coursework, presentations, literature review, programming projects, unseen examinations and term papers. The MSc project is assessed by a 12,000-word dissertation.

MSc in Intelligent Systems 1 year full time/2 years part time This MSc prepares you for research and development in intelligent systems, covering theoretical issues and practical techniques for their design and implementation. Programming skills are developed through an introductory module in Java, enabling students from both computing and non-computing backgrounds to access a wide range of specialist options commensurate with their experience. You can choose to organise your studies around these themes:

• adaptive systems • artificial intelligence • creative systems

• computational neuroscience. Alternatively, you can devise your own interdisciplinary combination of modules according to your personal interests. Additional entry information Applicants should have a background in computing, cognitive subjects (such as neuroscience, psychology, linguistics or philosophy) or other disciplines requiring both numeracy and computer literacy.

Career paths

Our graduates have gone on to pursue careers in software development, systems analysis, and technical communication. Employers of our graduates include Logica, Sony, Siemens and American Express. A high proportion of our graduates go on to undertake research degrees at Sussex and other prestigious universities. Course structure

Autumn term: Applied Natural Language Processing • Intelligent Systems Techniques • Object-Oriented Programming (students with a high level of programming experience may take Advanced Software Engineering). You also choose one option from Artificial Life • Intelligence in Animals and Machines • Mathematics and Computational Methods for Complex Systems • Real-World Cognition • Web Computing.

Spring term: Image Processing • Machine Learning. You also choose two options from Adaptive Systems • Computational Neuroscience • Generative Creativity • Neural Networks • Neuroscience of Consciousness • Technology-Enhanced Learning Environments. Summer term: you undertake a dissertation project under faculty supervision. There may be opportunities to collaborate in this with an industrial partner. The dissertation offers scope to specialise through research in a chosen topic, and the work of some projects has led to publication in journals and conference proceedings.

Assessment

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

MSc in Information Technology with Business and Management 1 year full time/2 years part time This course explores the many ways in which information technology supports and enables business and management activity and processes. You can choose to organise your studies around these themes:

• business and management • human systems

• managing innovation • software engineering.

Alternatively, you can devise your own combination of modules according to your personal interests.

Applicants with a good background in computing, information technology, engineering or other subjects where programming is a key element are suited to this course. Applicants with good degrees in business or with relevant industrial experience of programming have also been successful.

Career paths

Many of our graduates have gone on to careers in the banking and energy sectors, while others have gone on to pursue careers as IT consultants, project managers, software professionals and other roles in the IT sector. Employers of our graduates include HSBC, Bangkok Bank, KPMG, G4 Analytics and RDF Group. Successful completion of the degree also opens up the opportunity for further study at PhD level.

Broadcast-quality lecture capture for experiments in digital pedagogy

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Part-time courses

The part-time structure for each course 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: in each of the autumn and spring terms you take two modules. In the spring and summer terms you complete work on the dissertation. Research courses

MPhil, PhD in Cognitive Science MPhil, PhD in Informatics

As a research student, you are associated with one or more research groups in the Department of Informatics and allocated a computer and working area in comfortable shared offices. You have full access to your research group’s specialist facilities and laboratories. The Department is engaged in a wide range of highly rated research, covering many areas of artificial intelligence, computer science and cognitive science. We can supervise in all areas of faculty specialism.

Applicants wishing to pursue interdisciplinary research involving artificial intelligence (AI), including computational philosophy of mind or AI of biology, may apply to do research degrees in cognitive science.

Career paths

Many of our graduates have continued in academia as postdoctoral researchers, lecturers and assistant professors at institutions throughout the UK and worldwide. Other graduates have embarked on careers in industry as scientific officers, project leaders, managers, developers and system analysts in a diverse range of businesses from small specialist outfits to multinational companies such as Morgan Stanley and Microsoft.

Research/industry links

Research is motivated by social, economic and industrial needs. Strong links have been developed with local and national industry – not least because most practical problems requiring research also demand an interdisciplinary approach. These relationships are further exemplified in the University’s Innovation Centre, where several of the companies are drawing on research carried out at Sussex.

Supervision and review of progress Students are assigned two supervisors for the duration of their studies. They meet their primary supervisor regularly on an informal basis, and for a documented review meeting every month. A formal review of progress is conducted each year. Research training

Students admitted to research courses take a Research Skills Development module in their first two terms, which is specifically designed for students in the School of Engineering and Informatics. In addition, specific MSc modules may be recommended to enhance your subject knowledge where necessary.

The University’s Doctoral School runs a wide range of training courses covering the needs of students throughout all phases of their studies. Visit www.sussex.ac.uk/doctoralschool

Academic activities

Research students make a substantial contribution to the research output of the Department of Informatics, and frequently present their work at conferences and in journals.

Postgraduate students are encouraged to attend and give talks in the various specialised seminar series in the Department. In addition to the seminar series run by each research group, there are seminar series run by other disciplines and the interdisciplinary research centres, which students regularly attend.

Recent thesis titles

A framework for the design, prototyping and evaluation of mobile interfaces for domestic environments

An inertial motion capture framework for constructing body sensor networks Automated reasoning for reflective programs Bio-inspired approaches to the control and modelling of an anthropomimetic robot Biometric storyboards: a games user research approach for improving qualitative evaluations of player experience

Chaotic exploration and learning of locomotor behaviours

Cognitive modelling of complex problem-solving behaviour

Data-driven techniques for animating virtual characters

Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application

Evaluation of the usability of constraint diagrams as a visual modelling language

Graph-based approaches to word sense induction

Individual differences in synaesthesia: qualitative and fMRI investigations on the impact of synaesthetic phenomenology

Model development and analysis techniques for epidemiological and neurobiological dynamics on networks

Module hierarchy and centralisation in the anatomy and dynamics of human cortex Neuronal oscillations, information dynamics, and behaviour: an evolutionary robotics study Video analytics for security systems Research groups

Measuring changes in the brain’s activity using electroencephalography (EEG) and transcranial magnetic stimulation techniques

MSc in Management of Information Technology

1 year full time/2 years part time This MSc equips you with the skills to analyse information technology needs and to devise innovative solutions in companies and other organisations with complex and demanding information technology (IT) system requirements. You learn how to design, evaluate and apply information technology systems in a business setting – taking account of human, organisational and strategic factors. You explore the concepts and principles of IT systems and their interfaces, and the theories and techniques relating to the management of IT as an innovative and strategic resource in an organisation. You work on individual and group-based projects, and develop skills in:

• researching current practice

• analysing IT system trends, methodologies and interfaces

• communicating concepts, designs and evaluation within a technical environment. You will be engaged in a range of activities to help your learning, including lectures, seminars, discussions, directed reading, role play and peer review.

This interdisciplinary course is taught jointly in the Department of Informatics and the Department of Business and Management, by staff specialising in computer science and information technology systems, as well as management and technology innovation. Additional entry information

Applicants should have an academic background with substantial computing, information technology, science, technology or business-related content.

Career paths

This MSc prepares you for roles requiring an integrated understanding of the internal and external business context, the factors influencing successful IT innovation, the opportunities presented by new kinds of information technology in business, and the successful planning and deployment of IT systems. There is a global shortage of IT professionals. This course provides a strong theoretical and practical preparation for a career in this area.

Autumn term: Change and Leadership • E-Business and E-Commerce Systems • Human-Computer Interaction • Management Innovation and Organisational Performance • Personal and Professional Development. Spring term: Business in Context (Europe or Asia) or Business Context in Emerging Economics • HCI Advanced Topics • Managing Complex Projects and Systems • Strategic Management. Summer term: you undertake supervised work for the MSc dissertation.

Assessment

Assessment methods include unseen examinations, reports of various lengths, individual and group presentations, and learning diaries.

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Faculty research interests include:

Dr Luc Berthouze Mathematical neuroscience, networks, dynamical systems, motor

development.

Professor Margaret Boden Computational approaches in the philosophy of mind and psychology, purpose and creativity. Dr Chris Buckley Modelling cognition from a situated, embodied and dynamic perspective. Dr Ron Chrisley Non-conceptual

representation; philosophy of cognitive science, AI, mind, consciousness, computation. Professor Phil Husbands Evolutionary and adaptive robotics, evolutionary computation, ALife, computational neuroscience. Professor Thomas Nowotny Information processing in nervous systems, sequence learning in neuronal systems.

Dr Andy Philippides Computational neuroscience and neuroethology, evolutionary robotics, insect visual homing strategies. Professor Anil Seth Theoretical neuroscience and evolutionary and adaptive systems, consciousness science.

Dr Chris ThorntonComputational 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. Dr Ian Mackie Applying techniques from mathematical logic and quantum mechanics to programming language implementation. Dr George Parisis Datacentre networking and storage, information-centric networking, publish/ subscribe systems, distributed systems. Dr Bernhard Reus Mathematical semantics of programming languages and their foundations; constructive logic.

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

We are interested in all types of user, ranging from experts using technology in their work (such as medical professionals) and experts developing technology for their work (such as programmers) to people using technology for entertainment and leisure purposes (such as gamers) and to novices of all kinds (from children using educational technology to adults using social technology). Our current research focuses on areas including human-centred design, computer graphics, technology-enhanced learning, digital heritage, motion-sensing technologies, digital content creation, digital economy and data analytics. Faculty research interests include:

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

Dr Judith Good Constructivist learning environments, game-based learning, technology toolkits for learning.

Dr Kate Howland Game creation for learning, interactive storytelling, external representations in educational software.

Professor Ann Light Interaction design, digital tools in mobile and ubiquitous contexts. Dr Paul Newbury Multimedia systems, virtual prototyping, digital content creation, technology-enhanced learning.

Dr Marianna Obrist Touch and touch-less interaction with technology, smell and taste interaction modalities.

Dr Phil Watten Virtual prototyping, high-level design, system modelling, display systems, media production, web broadcasting.

Dr Martin White 3D graphics, virtual, augmented and mixed reality, animation, motion sensing, motion gaming, digital heritage systems. Interdisciplinary research centres The Department 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 by 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. Members include researchers and students in artificial intelligence, psychology, linguistics, neuroscience and philosophy.

Sackler Centre for Consciousness Science (SCCS)

SCCS is a collaboration between the Department of Informatics, the School of Psychology, and 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. Research groups

Research is a core activity of the Department of Informatics and is organised around four 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 www.sussex.ac.uk/informatics). Cognitive and 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. Areas of specific interest include classifying large volumes of natural language text (eg free text in medical records), mining opinions from social media, developing machine learning methods for non-standard learning settings, creating novel visualisations of large and complex datasets, cognitive modelling of processes such as attention and graphical production, and designing cognitively informed interactive tools for complex problem-solving and decision making.

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 cognitive science of representational systems, processes of writing and drawing.

Dr Bill Keller The use of language technology to support communication and interaction, language-aware technology.

Dr Novi Quadrianto Machine learning for internet-scale applications, non-parametric structured prediction, kernel methods. Professor David Weir Controlling non-determinism in natural language generation, language in pervasive computing environments. Dr Sharon Wood Multi-agent systems, cognitive modelling, 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 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, 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 major cross-campus initiatives.