Course summary
Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges the scientific community is currently working on. Computational cognitive neuroscience is a young and exciting discipline that tackles these long-standing research questions by integrating computer modelling with experimental research. This Masters programme will foster a new generation of scientists who will be trained in both neuro-computational modelling as well as cognitive neuroscience. Its core topics include:
- Creating computational/mathematical models of neurons, circuits and cognitive functions
- The fundamentals of cognitive neuroscience (brain mechanisms and structures underlying cognition and behaviour)
- Advanced data analysis and neuroimaging techniques
- This cutting-edge programme is at the forefront of a new, rapidly emerging field of research.
- It is multidisciplinary, conveying the theory and practice of computational and cognitive neurosciences.
- You can do your final research project in collaboration with a variety of international companies, paving the way for employment and internship opportunities. Currently, our panel of industrialists includes representatives from Sony Japan, Bayer, Filament, LiquidWeb, and DeepWave Technologies (Please note that this list of collaborators may change and that the implementation of a joint project with them is subject to their availability).
- Graduates of this programme will gain a competitive edge in the job market over graduates of other, standard programmes in related fields.
Modules
You will study the following compulsory modules: Foundations of Neuroscience Statistical Methods 15 credits Cortical Modelling 15 credits Cognitive Neuroscience 15 credits Modelling Cognitive Functions 15 credits Advanced Quantitative Methods 15 credits You will also undertake a 60 credit research project investigating an aspect of cognitive neuroscience using computational modelling, advanced data analysis methods, or a combination of these techniques. Culminating in a 10,000 word dissertation, the project will be carried out by combining the computational, experimental and data analysis skills that students will acquire over Term 1 and 2. Option modules You will choose one option from the following two modules. Data Programming 15 credits Introduction to coding with MATLAB 15 credits You will also choose one of the following options. Neural Networks 15 credits Machine Learning 15 credits Research Design and Analysis 15 credits Critical Analysis 15 credits Physical Computing 1 15 credits Behavioural Genetics 15 credits Artificial Intelligence 15 credits Please note that due to staff research commitments not all of these modules may be available every year.
Entry requirements
First or upper second-class honours degree (or equivalent undergraduate degree) in a relevant discipline. Applicants might also be considered if they aren’t a graduate or their degree is in an unrelated field, but have relevant experience and can demonstrate the ability to work at postgraduate level. A levels in Computer science or Science or Maths. Applications will be reviewed on a case-by-case basis. Depending on previous background and experience, applicants may be required to take one or more pre-sessional courses (for example in programming, statistics, or maths) prior to the start of the programme. These courses will be free to MSc offer holders. If English isn’t your first language, you will need an IELTS score (or equivalent English language qualification) of 6.5 with a 6.5 in writing and no element lower than 6.0 to study this programme.
Fees and funding
Tuition fees
No fee information has been provided for this course
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Provider information
Goldsmiths, University of London
New Cross
Lewisham
SE14 6NW