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It’s widely recognised by modern neuroscience that taking a systems approach to exploring the brain is vital to understanding brain function. Systems neuroscience focuses on the interactions between neural structures in networks that give rise to sensori-motor control and information processing, and it’s these interactions that provide us with a foundation for understanding the relationship between brain structure and brain function in the context of the cognitive, perceptual and motor mechanisms that underpin behaviour.
To develop our understanding of this relationship we need to integrate experimental and theoretical approaches. That’s why the MSc Systems Neuroscience course has been designed to provide you with interdisciplinary training in cutting-edge approaches to
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For this course, we usually ask for a 2:1 honours degree or equivalent qualification in either a life science (including psychology) or mathematical/physical science (including engineering).
We also accept qualifications from other countries. Find out which qualifications we accept from your country on our webpages for international students: View Website
If you have not already studied in a country where English is the majority language, it is likely that you will need to have an English language qualification. We usually ask for: International English Language Testing Service (IELTS): Overall grade of 6.5 with 6 in each component.
Up-to-date fees can be found on the University of Sheffield's webpages for postgraduate students: Please see the university website for further information on fees for this course.
University of Sheffield has grown in reputation and size to become one of the UK’s leading universities with a global reputation for teaching and research. As part of the UK Russell Group, the University is a premier-league, research-led institution with over 27,000 students including more than 7,000 international students from 143 countries and over 7,000 members of staff.Read more
"Computational Neuroscience brings together researchers in neuroscience, engineering and computing to name a few, and it is this interdisciplinary approach that first attracted me to the subject. I chose the MSc in Cognitive and Computational Neuroscience at Sheffield due to the diversity of course modules and strong research groups there, such as the adaptive behaviour research group and Neurovascular and Neuroimaging Research Group.
"The course itself has a taught aspect with modules in the first and second semester, followed by an independent research project over the summer. The modules are taught in a mixture of lectures, discussion groups and computer lab classes. The smaller number of fellow students in lectures and labs means there is an opportunity to engage more closely with the lecturers to discuss the course materials. I was drawn to the course at Sheffield due to the variety in module topics. I had the opportunity to learn not only about computational modelling methods, but also imaging techniques such as fMRI and electrophysiology.
"After completing the taught modules, the summer period was dedicated to an extended research project where I could apply everything I had learned. I joined the Active Touch Lab, supervised by Dr Hannes Saal, to model cortical somatotopic representations using self-organisation algorithms. During the project I was able to apply the theoretical knowledge and programming techniques I learned in the modules to create a cortical model of touch processing. Dr Hannes Saal encouraged me to present my MSc work as a poster presentation at two scientific conferences. It was a great experience as I had the opportunity to network with other students and academics in my field.
"I received a departmental teaching fellowship following my MSc and have stayed on at Sheffield to complete my PhD with Dr Hannes Saal, enabling me to continue working on research questions that arose from my MSc thesis.
"I would strongly recommend the MSc to anyone who wants a comprehensive insight into both computational modelling and complimentary cognitive neuroscience techniques, such as neuroimaging."
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