The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. We are one of the UK’s largest and most prestigious academic teams in these fields.
We foster world-class interdisciplinary and collaborative research bringing together a range of disciplines.
Our research falls into three areas:
In machine learning we develop probabilistic methods that find patterns and structure in data, and apply them to scientific and technological problems. Applications include areas as diverse as astronomy, health sciences and computing.
In computational neuroscience and neuroinformatics we study how the brain processes information, and analyse and interpret data from neuroscientific experiments
The focus in the computational biology area is to develop computational strategies to store, analyse and model a variety of biological data (from protein measurements to insect behavioural data).
You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.
A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.
The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.
The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.
It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.
Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.
Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
The research you will undertake at IANC is perfectly suited to a career in academia, where you’ll be able to use your knowledge to advance this important field. Some graduates take their skills into commercial research posts, and find success in creating systems that can be used in everyday applications.
The Web Intelligence MSc aims to provide you with the knowledge and skills to solve challenging computational problems related to advanced reasoning systems for the internet. It will give you a broad understanding of web intelligence and a thorough knowledge of techniques for developing intelligent software.
The Web Intelligence MSc will provide you with the practical knowledge and expertise to evaluate, design and build intelligent software for the internet. You will complete the course in one year, studying September to September and taking a combination of required and optional modules totalling 180 credits, including 60 credits that will come from a research project and dissertation of 10,000 words. You will study Artificial Intelligence, Agents and Multi-agent Systems as well as Software Engineering of Internet Systems. There are also opportunities to explore a broad range of optional modules allowing you to develop a study pathway that reflects your interests.
A graduate in computer science, mathematics, science or engineering with good knowledge of computer programming, this MSc will provide you with the practical knowledge and expertise to enable you to evaluate, design and build intelligent software for the web. Research for your individual project will provide valuable preparation for a career in research or industry.
We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.
You are expected to spend approximately 150 hours of effort (i.e. about 10 hours per credit) for each module you attend in your degree. These 150 hours cover every aspect of the module: lectures, tutorials, lab-based exercises, independent study based on personal and provided lecture notes, tutorial preparation and completion of exercises, coursework preparation and submission, examination revision and preparation, and examinations.
The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project will be assessed through a dissertation.
Our graduates have continued on to have very successful careers in industry and research. Recent employers have included general software consultancy companies, specific software development businesses and the IT departments of large institutions (financial, telecommunications and public sector). Some graduates have entered into the field of academic and industrial research in software engineering, bio-informatics, algorithms, artificial intelligence and computer networks.
The MSc in Computational Finance will introduce students to the computational methods that are widely used by practitioners and financial institutions in today's markets. This will provide students with a solid foundation not only in traditional quantitative methods and financial instruments, but also scientific computing, numerical methods, high-performance computing, distributed ledgers, big-data analytics, and agent-based modelling. These techniques will be used to understand financial markets from a post-crisis perspective which incorporates findings from the study of financial markets at high-frequency time scales, modern approaches to understanding systematic risk and financial contagion, and disruptive technologies such as distributed-ledgers and crypto-currencies. The programme is highly practical, and students will have the opportunity to apply their learning to real-world data and case studies in hands-on laboratory sessions.
Computational Finance studies problems of optimal investment, risk management and trade execution from a computational perspective. As with any engineering discipline, computational finance analyses a given problem by first building a model for it and then examining the model. In computational finance, however, our model is typically analysed by running computer programs, rather than solving mathematical equations. In addition to standard computational methods such as Monte-Carlo option pricing, you will also learn more advanced modelling techniques such as agent-based modelling, in which the model itself takes the form of a computer program.
The programme will provide a foundation in the core skills required for successful risk management and optimal investment by giving a grounding in the key quantitative methods used in finance, including computer programming, numerical methods, scientific computing, numerical optimisation, and an overview of the financial markets. You can then go on to study more advanced topics, including the market micro-structure of modern electronic exchanges, high-frequency finance, distributed-ledger technology and agent-based modelling.
Students are expected to go in to careers such as Investment Banking, Hedge Funds and Regulatory Bodies.