MRes Natural Computation - 2022

Educational Aims Of Programme

• Meet the increasing need from industry for graduates equipped with a knowledge of natural computation techniques.
• Provide a solid foundation in natural computation for graduates to pursue a research and development career in industry or to pursue further studies (e.g. PhD).
• Give up-to-date coverage of current topics in natural computation (such as evolutionary algorithms, co-evolution, evolutionary design, nature-inspired optimisation techniques, evolutionary games, novel learning algorithms, artificial neural networks, the theory of natural computation).

Programme Outcomes and Learning, Teaching and Assessment Strategies

Knowledge and Understanding

• The ideas and concepts underlying a variety of natural computation techniques.
• The strength and weakness of natural computation techniques and the similarities and differences between these techniques and other existing techniques.
• Applications of these techniques to solve large and complex problems in industry.

Skills & Other Attributes

• Given a real-world problem, identify whether natural computation techniques are likely to provide a good solution and then select appropriate techniques from those available.
• Derive efficient solutions to appropriate non-trivial problems using natural computation techniques alone or in combination with other techniques and implement these solutions using both 'off the shelf' software and software they themselves write.
• By the end of the programme, carry out original research and development (e.g. in industry or for a subsequent PhD) with limited supervision, both in the field of natural computation and in allied fields
• Use appropriate methods for literature searching and information retrieval
• Know and apply a variety of research methods, including experimental design and the analysis of data

Transferable Skills

Footnotes