Master of Research - Natural Computation

There is an increasing need from industry for professionals with knowledge of natural computation techniques. Graduates from our Natural Computation Master of Research (MRes) develop a solid foundation to pursue a research and development career in industry or further studies.

This multidisciplinary area is the study of computational systems that use ideas and gain inspiration from natural systems. The MRes programme explores 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 and theory of natural computation.

The Natural Computation MRes is a Masters degree by research. This means that students are taught core principles and then develop these skills by doing interesting, innovative research, supported by academic staff and peers. This is structured so that students learn how to plan, organise and manage their time; students learn what it is to be a scientific researcher; students help contribute to the development of new knowledge; students learn intellectual skills such as argumentation, exposition, and reasoning; and students develop as an individual by improving their communication skills, writing, collaborative working and creativity.

The mini project module consists of a research project on the in-depth investigation of a chosen topic coming from industry (strongly encouraged) or academia.

The compulsory Research Skills module provides students with the basis of transferable knowledge and skills necessary for a successful research-oriented career in industry or academia, with a particular orientation to computing-based disciplines.

The research thesis project consists of solving a substantial problem using natural computation techniques (including hybrid techniques). Industrial co-supervisors are used whenever appropriate, and students will be required to apply the knowledge and skills they have acquired to solve a difficult problem.