Course summary
The Cognitive Neuroimaging and Data Science MSc helps to provide fundamental insight into important theories in cognitive and computational neuroscience, and hands on experience in methods of neuroimaging and data science techniques. To understand the brain and performance, there is need to merge the traditional, hypothesis-based experiments with unbiased, large-scale machine learning approaches to study the dynamic interactions between brain regions and its relations to behaviour. This MSc offers advanced learning in two different pathways 1) Cognitive Neuroscience and 2) Computational Neuroscience. For your studies and research, you will have access to various neuroimaging tools (for example, MRI, MEG, EEG, brain stimulation and fNIRS) housed in the Centre for Human Brain Health. You will develop important skills associated with proactive problem solving and analysing big (neuroscientific) data. You will have the opportunity to interact with a broad range of researchers (from the Centre for Human Brain Health, School of Psychology and Computer Science) who will help you develop specific interests and skills within cognitive neuroimaging and data science.
Modules
The course comprises of a series of taught core and optional modules. The core modules are designed to promote development of skills in experimental design, data science and analysis, and scientific writing. Several core modules are shared across the two pathways, but some are specific to either the cognitive or computational neuroscience pathway Research Methods & Skills in Psychology Proposing Research Cognitive Neuroscience Methods & Applications (cognitive neuroscience pathway) Data Science for Behaviour and Brain I (cognitive neuroscience pathway) Mind, Brain, Models (computational neuroscience pathway) Optional modules are shared across MSc programmes in the School of Psychology. Examples of optional modules available at this moment are: Translational Cognitive Neuroscience Fundamentals in Brain Imaging Application of Electrophysiological Approaches in Cognitive Neuroscience Modelling Development and Diversity Introduction to Computational Methods (computational neuroscience pathway) Data science for behaviour and brain I and II Students on the computational neuroscience pathway can also take specific modules from Computer Science. For example: Intelligent Robotics Neural Computation Machine Learning and Intelligent Data Analysis Advanced Robotics Robot Vision Finally, students undertake a supervised research project, leading to a 6,000-word research thesis. Please note: The modules listed on the website for this programme are regularly reviewed to ensure they are up-to-date and informed by the latest research and teaching methods. Unless indicated otherwise, the modules listed for this programme are for students starting in 2023. On rare occasions, we may need to make unexpected changes to compulsory modules after that date; in this event we will contact offer holders as soon as possible to inform or consult them as appropriate.
Assessment method
The way that the different assessments have been designed for the MSc programme is to ensure that your studies help you to develop essential skills that are transferrable to future employment. As such, you will be assessed in a variety of ways. Each assessment is tailored to each module and the material offered within the courses but may include essays and reports, oral and poster presentations, programming projects, scripting assessments, and peer reviews.
Entry requirements
Applicants should have obtained at least a 2:1 Honours degree in a relevant subject (eg, Psychology, Neuroscience, Computer Science, Physics, Engineering or Mathematics). With respect to the Cognitive Neuroscience pathway, applicants should have gained at least a 2:1 (or equivalent) in the research dissertation (i.e. experience of planning and conducting research and analysing data). Applicants who do not meet our requirement for a 2:1 in their final-year research project, but who have gained significant research experience in a cognitive neuroscience research lab(s) will be considered on a case-by-case basis. With respect to the Computational Neuroscience pathway, you must have a strong interest in learning in an interdisciplinary environment and must have substantial quantitative skills. Programming skills in Python, Matlab, Java, and/or C are desirable.
Fees and funding
Tuition fees
No fee information has been provided for this course
Additional fee information
£10,170 FT (UK students)
£24,750 FT (International students)
Provider information
University of Birmingham
Edgbaston
Birmingham
B15 2TT