Scientific and Data Intensive Computing MSc
Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Numerical methods can only play an even more important role in the future as we face even bigger challenges. Therefore, skilled scientific programmers are in high demand in industry and academia and will drive forward much of the future economy.
UK tuition fees (2023/24)
Overseas tuition fees (2023/24)
Normally a first-class Bachelors degree in science, engineering or a related subject and with a strong interest in computing or an overseas qualification of the equivalent standard. Students with a first degree in Finance, Management, Actuarial Science or related subjects will not normally be accepted.
If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.
The English language level for this programme is: Level 2
UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level. International Preparation Courses
Further information can be found on our English language requirements page.
Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.
International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.
About this degree
This programme aims to provide a rigorous formal training in computational science to produce highly computationally skilled scientists and engineers capable of applying numerical methods and critical evaluation of their results to their field of science or engineering. It brings together best practices in computing with cutting-edge science and provides a computing edge over traditional science, engineering and mathematics programmes.
You can find additional information on this degree and its content on our MSc FAQ page.
Who this course is for
This programme is suitable for students with motivated and inquisitive minds who have a background in science, engineering or a related subject, and a strong interest in computing. Some experience in programming is essential.
What this course will give you
UCL is consistently placed in the global top 20 across a wide range of university rankings. The degree is associated with UCL’s Centre for Data Intensive Science and Industry, which is hosted by the department of Physics and Astronomy. The Centre also runs a highly successful Centre for doctoral training hosting over 50 PhD students.
UCL Physics & Astronomy is among the top departments in the UK for this subject area: UCL is consistently placed in the global top 20 across a wide range of university rankings – and is currently 4th in the UK in the QS World University Rankings by Subject 2022 for Physics & Astronomy.
Our wide-ranging expertise provides opportunities for ground-breaking interdisciplinary investigation. World-leading experts in the field and students benefit from a programme of distinguished visitors and guest speakers in many scientific seminars. In this way, a network of collaborators, mentors and peers is created, which students can access in their future careers.
This degree has been designed to balance professional software development and high-performance computing skills with a comprehensive selection of numerical mathematics and scientific subjects, culminating in a scientific computing dissertation project. The dual aspect of a science and computing degree enables students to tackle real-life problems in a structured and rigorous way and produce professional software for their efficient solution.
The foundation of your career
Students develop a comprehensive set of skills which are in high demand both in industry and academia: professional software development skills including state-of-the-art scripting and compiled languages; knowledge of techniques used in high-performance computing; understanding and an ability to apply a wide range of numerical methods and numerical optimisation; a deeper knowledge of their chosen science subject; oral and written presentational skills.
Our alumni who successfully completed the programme last year have all moved on to pursue full-time employment with reputable international organisations holding prominent positions, including Data Scientists, Data and Software Developers, Software Engineers, Data Analysts, Qualitative Researchers or Technologists. Over half of the alumni indicated that attaining a qualification in Scientific and Data Intensive Computing helped them secure their current employment. In addition, a few alumni have also pursued further studies with top-ranking universities or have stayed at UCL to complete their PhD research. Similarly, those pursuing PhD research had indicated that the qualification had helped them to gain entrance into top-ranking universities. (Programme Graduate Outcome Survey, 2022.)
Over half of the alumni agreed that they are utilising what they had learnt on the programme in their further studies or at the workplace (Programme Graduate Outcome Survey, 2022).
We expect our graduates to take up exciting science and engineering roles in industry and academia with excellent prospects for professional development and steep career advancement opportunities. This degree enables students to work on cutting-edge real-life problems, overcome the challenges they pose and so contribute to advancing knowledge and technology in our society.
Teaching and learning
The programme is delivered through a combination of lectures and hands-on programming and includes a variety of short programming projects, delivered as part of the taught component. Students are encouraged to participate in scientific seminars, for example, weekly seminars at the UCL Centre for Inverse Problems. Assessment is through examinations, assignments, small projects and the dissertation, including a computer programme.
A 15-credit module consists of around 150 hours of learning time, and for a lecture module typically includes 20-30 hours of contact time, plus engagement with online materials asynchronously, and personal study time.
The research-project module is 60 credits, and consists of around 600 hours personal study time alongside approximately 15-20 hours contact time.
The programme is made up of modules to the value of 180 credits. The programme consists of a dissertation/report (60 credits) plus either 6 optional core modules (90 credits) and 2 elective modules (30 credits) or a research essay (30 credits), 5 optional core modules (75 credits) and 1 elective module (15 credits).
Optional core modules cover topics in Advanced Programming, Model Building and Optimisation, Machine Learning and Data Statistics. Students can choose from a large selection of elective modules across the faculties of MAPS and Engineering. These modules should be chosen to support the individual projects.
Term One: students should take 3 or 4 taught modules from among their choice of 6 or 8 taught modules. These could be optional and elective modules.
Term Two: students should take the remaining of their 6 or 8 taught modules, which could be optional or a combination of optional and elective modules.
In addition, students taking research essays will work on their essay during the first and second terms, and must submit their literature review at the end of Term Two.
Term Three: students will focus full-time on their individual research project consisting of a supervised topic and a written project report submitted at the end of August. As part of the project report, students may submit documented code through a public repository, including some unit testing and must present their individual projects in September.
The programme is made up of modules to the value of 180 credits. The programme consists of a dissertation/report (60 credits) plus either 6 optional core modules (90 credits) and 2 elective modules (30 credits) or a research essay (30 credits,), 5 optional core modules (75 credits) and 1 elective module (15 credits).
In Year One: students will take 4 (or more) taught modules from among their choice of 6 or 8 taught modules. These could be optional and elective modules.
In Year Two: students will take the remaining of their taught modules, which could be optional or a combination of optional and elective modules. Students taking the research essay may complete this during either Year One or Year Two.
Students will focus on their individual research project consisting of a supervised topic and a written project report submitted at the end of August. As part of the project report, students may submit documented code through a public repository, including some unit testing and must present their individual projects in September.
Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability is subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.
Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Scientific and Data Intensive Computing.
Fees and funding
Fees for this course
|Tuition fees (2023/24)||£14,100||£7,050|
|Tuition fees (2023/24)||£35,000||£17,500|
The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees.
There are no programme-specific costs.
For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.
Funding your studies
Students can be self-funded or find sponsorship from alternative sources, for instance via those shown on the UCL scholarships and funding pages.
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.
Deadline: 8 June 2023Value: £15,000 (1 year)Criteria Based on both academic merit and financial needEligibility: UK
There is an application processing fee for this programme of £90 for online applications and £115 for paper applications. Further information can be found at Application fees.
When we access your application we would like to learn:
- why you want to study Scientific and Data Intensive Computing at graduate level
- why you want to study Scientific and Data Intensive Computing at UCL
- what particularly attracts you to the chosen programme
- how your academic and professional background meets the demands of this challenging programme
- where you would like to go professionally with your degree
Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.
Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.
Choose your programme
Please read the Application Guidance before proceeding with your application.
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