Computational Cognitive Neuroscience Goldsmiths, University of London

Overview

Why Computational Cognitive Neuroscience at Goldsmiths?

Goldsmiths, University of London, is renowned for its interdisciplinary approach, ranking highly in cognitive science and neuroscience education. The MSc in Computational Cognitive Neuroscience stands out due to its integration of computer modelling with experimental research, preparing students for the rapidly evolving job market. The programme fosters strong partnerships with industry leaders, offering students opportunities to collaborate on projects that enhance their employability. Facilities are equipped with cutting-edge technology, ensuring students gain hands-on experience in advanced data analysis and neuroimaging techniques.

Tuition Fee Breakdown

The tuition fees for the MSc in Computational Cognitive Neuroscience are as follows:

• International students: £20,000 per year
• Home students: £13,600 per year

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum is designed to cover essential topics in computational cognitive neuroscience, and students will engage with both compulsory and optional modules. The compulsory modules include:

• Foundations of Neuroscience (15 credits)
• Multivariate Statistical Methods (15 credits)
• Cortical Modelling (15 credits)
• Cognitive Neuroscience (15 credits)
• Modelling Cognitive Functions (15 credits)
• Advanced Quantitative Methods (15 credits)
• Research Project in Computational Cognitive Neuroscience (60 credits)

Students may also choose from optional modules such as:

• Introduction to Coding in R and MATLAB (15 credits)
• Data Programming (15 credits)
• Critical Analysis (15 credits)
• Research Design & Analysis (15 credits)
• Machine Learning (15 credits)
• Artificial Intelligence (15 credits)
• Neural Networks (15 credits)

Careers with Computational Cognitive Neuroscience

Graduates of the MSc in Computational Cognitive Neuroscience have a diverse array of career paths available to them. They often find roles in academia, engaging in teaching and research, or in the technology sector as machine learning engineers or data scientists. Other opportunities include:

• Clinical engineering, focusing on the design and maintenance of medical equipment
• Communications engineering, developing new communication technologies
• Data analysis across various sectors, providing insights through data
• Programming and software development in fields such as games design and Human-Computer Interface (HCI) design
• Scientific research in health and pharmaceutical industries, as well as neural network applications

Additionally, many graduates pursue further academic study, such as PhDs in related fields, supported by the comprehensive career services offered at Goldsmiths. The programme's links with industry partners also facilitate valuable internship opportunities, enhancing the employability of its graduates.