7Dec
PostgraduateCourse summary
Why study MSc Computational Cognitive Neuroscience at Goldsmiths Understanding the relationship between brain, cognition and behaviour is one of the biggest challenges for the scientific community. This established Masters course, integrating computer modelling with experimental research, equips students with a solid theoretical basis and practical experience of advanced data analysis and experimental techniques in computational and cognitive neuroscience.
- This cutting-edge Masters is at the forefront of a new, rapidly emerging field. It will help you develop a unique set of complementary skills, making you extremely competitive in securing data analyst or research positions in both industry and academia.
- The MSc is highly multidisciplinary, covering the theory and practice of computational and cognitive neurosciences. Areas of application range from machine learning to brain-computer interfaces, to research in cognitive and clinical neuroscience.
- We have strong links with industry. You can decide to carry out your final research project in collaboration with one of our industry partners and collaborators, paving the way for employment and post-Masters internship opportunities.
- We welcome applicants from a variety of disciplines including psychology, computing, neuroscience, engineering, biology, maths and physics. There is no need to have prior experience in programming to apply.
Modules
You will study the following compulsory modules: Foundations of Neuroscience Multivariate Statistical Methods Cortical Modelling Cognitive Neuroscience Modelling Cognitive Functions Advanced Quantitative Methods Research Project in Computational Cognitive Neuroscience Optional modules You'll then have the option to take one, or both of the following optional modules: Introduction to coding in R with MATLAB or Data Programming If you choose just one of these modules, then you can also choose an additional option from a list published on an annual basis by the department. Recent optional modules include: Critical Analysis Research Design & Analysis Machine Learning Artificial Intelligence Neural Networks 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 (including computer science, engineering, physics, mathematics, statistics, biology, psychology, medicine) or closely related field. 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 (or equivalent) in science, computer science or mathematics. 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
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
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