Scientific and Data Intensive Computing UCL

Overview

UCL is renowned for its excellence in the field of Physics and Astronomy, consistently ranking within the global top 20 universities. The university's Physics & Astronomy department holds the 4th position in the UK according to the QS World University Rankings by Subject for 2024. The MSc in Scientific and Data Intensive Computing is closely associated with UCL's Centre for Data Intensive Science and Industry, which has hosted numerous PhD candidates since its inception. This collaboration facilitates groundbreaking interdisciplinary research and provides students with access to a network of leading experts and industry connections, enhancing their educational experience.

For the 2025/26 academic year, the tuition fees are as follows:

• UK students: £16,000 per year
• International students: £39,800 per year

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

The MSc programme comprises a total of 180 credits, structured as follows:

• Research Essay (30 credits)
• Five Optional Core Modules (75 credits)
• One Elective Module (15 credits) or a Dissertation/Report (60 credits)

Students will explore a variety of topics including:

• Advanced Programming
• Model Building and Optimisation
• Machine Learning and Data Statistics
• Numerical Optimisation
• Techniques of High-Performance Computing
• Research Software Engineering with Python
• Numerical Methods
• Computational and Simulation Methods

The curriculum is designed to provide a blend of theoretical knowledge and practical application, culminating in a significant research project.

Graduates of this MSc programme are well-prepared for diverse roles in both industry and academia. Alumni have successfully secured positions as Data Scientists, Software Engineers, Data Analysts, and Technologists with reputable international organisations. The Programme Graduate Outcome Survey from 2022 revealed that 90% of respondents credited their qualification in Scientific and Data Intensive Computing as pivotal in securing their current roles, with all respondents either employed or engaged in further studies within six months post-graduation. This degree opens doors to exciting opportunities in fields such as physics, biology, engineering, and environmental science, equipping graduates with the skills necessary to address real-world challenges.

The programme employs a mix of lectures, hands-on programming, and short projects. Assessment methods include examinations, assignments, and a dissertation that incorporates a programming component. Full-time students typically experience around 8-10 contact hours per week, complemented by substantial self-directed study. The structure is designed to ensure that students not only gain theoretical knowledge but also practical skills that are essential in the workforce.

Students are encouraged to engage with various networking opportunities throughout the programme, including participation in scientific seminars and collaborations with the Centre for Doctoral Training in Data Intensive Science. These interactions foster relationships with peers and mentors, which can be invaluable for future career developments.