MSc Computational Intelligence and Computational Biology
- Programme director
- Yaochu Jin
- Programme length
- Full-time: 12 months
- Programme start date
- September 2013
Foster your interest and receive fundamental and up-to-date knowledge for performing research in this interdisciplinary area.
Programme overview
This programme benefits greatly from the Department’s world-leading interdisciplinary research on computational intelligence, computational biology and computational and cognitive neurosciences, providing you with academic training in these areas. This training should foster your interest and provide you with fundamental and up-to-date knowledge for performing research in the interdisciplinary area. This programme also aims to provide students with hands-on technical skills that are needed for finding employment opportunities in industry and research institutes involved in research and development in intelligent optimisation and control, bioinformatics, brain research and computational biology.
In addition, the programme is run in close collaboration with the Faculty of Health and Medical Sciences.
Entry requirements
Candidates should have a Bachelors degree in computer science, mathematics, electrical engineering or physics. Students from neuroscience, bioscience and other related disciplines who have an adequate mathematical and computing background are also encouraged to apply. Candidates should have obtained a minimum 2.1. In exceptional circumstances, relevant work experience may also be considered if the candidate has achieved less than upper second.
English language requirements
IELTS minimum overall: 6.5
IELTS minimum by component:
6.0
Fees and funding
All fees are subject to increase or review for subsequent academic years. Please note that not all visa routes permit part-time study and overseas students entering the UK on a Tier 4 visa will not be permitted to study on a part-time basis.
| Programme name | Study mode | Start date | UK/EU fees | Overseas fees |
|---|---|---|---|---|
| MSc Computational Intelligence and Computational Biology | Full-time | Sept 2013 | £6,720 | £15,160 |
Funding
The Department pays a scholarship of £1,000 to students with a first-class honours degree or equivalent, who do not receive any other scholarship or bursary from the University. Please see the Department web pages for the full conditions.
Programme content
Compulsory Modules
- Brain–Computer Interface
- Bioinformatics and Bioinformatics Programming
- Computational and Cognitive Neuroscience
- Introduction to Computational Systems Biology
- Evolutionary Computation and Artificial Development
Optional modules include:
- Collective Intelligence
- Database and Knowledge Discovery
- Intelligent Information Systems
Compulsory Modules
Bioinformatics and Bioinformatics Programming
This module provides knowledge of the current bioinformatic analytical and prediction techniques for the analysis and interpretation of large-scale ‘-omics’ data sets central to the field of systems biology. Methods to be described include: genomics, for identifying genetic differences between species via sequence analysis and comparative genomic hybridisations (CGH); transcriptomics and chromatin immunoprecipitation on a chip (ChIP-chip), for the construction of putative gene regulatory networks via gene expression profiles, regulatory protein enrichment, clustering and promoter predictions; proteomics, for calculating protein abundance measurements and protein structure. An introduction to the statistical programming environment R and the programming language Perl will be included. In addition, a grounding in the principles of molecular biology, the founding biological science behind many high-throughput quantitative ‘-omics’ technologies, will be given.
Brain–Computer Interface
Brain–machine interface is a rapidly developing research area that greatly helps in understanding the functions of the brain, from generation of active potentials to modelling of various states of the brain. This module introduces the basic sensor technologies for capturing brain signals, the concepts of brain motor function, synchronisation and de-synchronisation of the brain, connectivity of brain regions, and the brain response to various stimuli (event-related and evoked potentials) by means of signal processing theory and methods. In addition, implications of neuro-feedback will be discussed and examined.
Computational and Cognitive Neuroscience
This module introduces the backgrounds of computational and cognitive neuroscience, including spiking models of neurons and neuronal networks, neurodynamics, learning algorithms such as Hebbian learning and spiking timing dependent plasticity. In addition, the main components of the brain involved in memory, cognition and behaviour control will also be described.
Introduction to Computational Systems Biology
This module describes the fundamental relationships and interactions between various parts of a biological object by which it is hoped that an understandable model of the whole system can be developed. The module will cover chemical foundation and enzymes, and fundamentals of molecular biology focusing on a systems level, by modelling the gene expression process, that is, the gene regulatory networks, methodologies for gene regulatory network, kinetic model of gene circuit, signal transduction, and dynamic signalling and gene expression regulation.
Evolutionary Computation and Artificial Development
Evolution and development are two areas where a systems approach can play an important role. On the basis of basic knowledge in systems biology, this module describes computational models for studying biological evolution and development.
Starting from a standard direct-coded evolutionary system, the module will discuss in detail how evolutionary developmental systems can be built and investigated in a computing environment. Then models for neural and morphological development will be presented. Possible engineering applications of such systems will also be discussed.
Optional modules include:
- Collective Intelligence
- Database and Knowledge Discovery
- Intelligent Information Systems
Teaching
Taught master’s programmes in the Department of Computing utilise our research-active staff in conjunction with state-of-the-art facilities. We provide a range of learning experiences, including lectures, tutorials, directed study, practical laboratories and project work, which prepare graduates for their professional life.
We are particularly keen to develop, in all our students, a broad range of generic skills to complement the core technical or scientific competencies of their chosen subject area. Our modular programme format, coupled with the increasing use of innovative teaching and learning strategies such as e-learning and industrially focused short courses, provides a flexible study environment whilst maintaining academic rigour and quality. Our record of graduate employment is outstanding, with Surrey graduates consistently being in high demand across all sectors.
Dissertation project
The MSc dissertation project makes up one third of the degree programme, starting at the end of the first semester and completing at the end of the summer. During the project, you are supervised by a member of academic staff to advise and guide you to completion. At the end of the project you must submit your bound dissertation, which forms a complete record of the project, which is then held in the University Library.
The project focuses in depth on a subject at the leading edge of computing. For example, projects can undertake the development of a software system to solve a particular problem, possibly in collaboration with an industrial partner.
Alternatively, projects can be research-based, in which case an aspect of computing is investigated, perhaps to evaluate particular techniques or propose a new algorithm. These projects are usually closely linked to the Department’s research strengths.
Whatever the topic, you are expected to develop a critical understanding of the methods and technologies needed, then implement and evaluate your chosen solution to a professional standard. Project planning and time management is an important part of the experience
Project examples
- Brain–computer interfacing based on neurofeedback
- Fast and robust feature extraction for detection of bootlegged museum images
- Modelling neural plasticity for spatiotemporal pattern recognition
- Predicting suitable vaccines for foot-and-mouth disease virus based on genetic sequence
- Reconstruction of global regulatory networks governing the production of antibiotics in Streptomyces coelicolor bacteria
- Semi-supervised learning for brain–machine interface
- Surrogate-assisted evolutionary optimisation of expensive problems
- Synthesis of genetic dynamics using evolutionary algorithms
Our degree programmes
The Department offers four MSc programmes. Each with its own distinct focus, all of them offer a taste of the Department’s specialisms.
Internet Computing, Security Technologies and Applications, and Computational Intelligence and Computational Biology are technical degrees requiring a solid background in computing or a cognate discipline.
The MSc in Information Systems is a more generalist degree, accepting students from a wider range of backgrounds. It takes a more high-level, overall view of information technologies and prepares students for managerial rather than technical roles in their future careers. It covers business and management topics as well as technical computing subjects.
The MSc in Security Technologies and Applications is specialised towards the Department’s multiple activities in relation to the technologies and principles that underlie a variety of information security techniques and technologies.
The MSc in Internet Computing is concerned with distributed information and computing resources, and builds from the Department’s activities relating to the Web and the Cloud. The programme also has a strong element of more general, technical computer science and software development skills.
The MSc in Computational Intelligence and Computational Biology is the latest addition to the portfolio of programmes, following the appointment of a Professor of Computational Intelligence and the subsequent growth of a nature-inspired computing theme in the Department.
All of the programmes benefit from the strong research community and industrial partnerships of the Department. In particular, the dissertation project allows students to work on a topic in one of the key research areas. Even though the programmes share many modules, each has its own focus and direction.
Regardless of which programme you choose, we are committed to making your year at Surrey a valuable and enjoyable experience.
Our department
The Department of Computing is an active department within the Faculty of Engineering and Physical Sciences. There are 19 full-time academic staff and around 400 students at all levels – from undergraduate through to PhD. The Department is proud of its friendly reputation and aims to provide a supportive environment for students.
The Computing degree programmes at the University of Surrey and the all-round student experience are highly rated in the National Student Survey and league table results. The undergraduate and postgraduate degree programmes are stimulating and challenging, with a high level of practical content. The Department is constantly exploring the use of new technology in teaching – such as podcasts and voting handsets – to support greater interactivity, accessibility and enjoyment of lectures. It also organises extra-curricular activities for those who want to explore other aspects of computing in more depth, while supporting local schools and colleges to bring some of the exciting aspects of computing to school pupils.
The Department’s research interests are many and varied, ranging across the research groups of Digital Ecosystems; Formal Methods and Security; Multimedia Security and Forensics; and Nature Inspired Computing and Engineering. With a strong research culture and a growing research profile, the Department of Computing has won several prizes, including the University Voting Systems Competition System Design award in 2007 and the prestigious Institution of Engineering and Technology Innovation in Engineering Security award in 2006.
Industry sponsors and prizes
The Department benefits greatly from strong links with industry, and our industry partners support the programme in various ways – some with guest lectures and some with prizes for the best student performance (typically £150–200 per prize).
Department links
Contact us
For general enquiries
0800 980 3200 or +44 (0)1483 681 681
For admissions enquiries
+44 (0)1483 686 050
