Home

Scientific and Data Intensive Computing MSc

London, Bloomsbury

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 students International students
Study mode
UK tuition fees (2026/27)
£16,800
£8,400
Overseas tuition fees (2026/27)
£42,700
£21,350
Duration
1 calendar year
2 calendar years
Programme starts
September 2026
Applications accepted
Applicants who require a visa: 20 Oct 2025 – 26 Jun 2026
Applications close at 5pm UK time

Applications open

Applicants who do not require a visa: 20 Oct 2025 – 28 Aug 2026
Applications close at 5pm UK time

Applications open

Apply for this course

Entry requirements

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.

The English language level for this course is: Level 1

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.

Further information can be found on our English language requirements page.

Equivalent qualifications

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 MSc programme offers an in-depth and rigorous training in computational science, designed to equip students with advanced computational skills applicable across a wide range of scientific and engineering disciplines. Combining state-of-the-art computational techniques with real-world scientific problems, this programme develops highly skilled computational scientists and engineers who can harness the power of numerical methods and data-intensive approaches to solve complex problems.

Students will gain expertise in key areas such as high-performance computing, data analytics, and advanced numerical simulations, all while learning to critically evaluate and interpret computational results in the context of their specific field. The programme stands at the intersection of traditional scientific disciplines and modern computing, giving students a competitive edge by integrating cutting-edge computational tools with scientific inquiry.

By bridging the gap between computing and scientific research, graduates will be well-prepared to tackle some of the most challenging problems in fields such as physics, biology, engineering, environmental science, and beyond. Whether pursuing a career in industry or academia, this MSc opens doors to roles that require deep technical knowledge, innovative problem-solving skills, and the ability to manage and interpret large-scale data sets.

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.

Read about what it takes to study for a Master's at UCL

What this course will give you

UCL Physics and 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 2025 for Physics and Astronomy.

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 77 PhD students since 2017.

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 department of Physics and Astronomy at UCL are proud holders of the Athena Swan Silver Award and achieved a Juno Champion Award from the Institute of Physics.

Read about what you'll get out of a graduate programme

The foundation of your career

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. 

In the Graduate Outcome Survey (2022), A strong majority of  respondents from this programme reported that earning a qualification in Scientific and Data Intensive Computing played a crucial role in securing their current employment, and agreed that they are utilising what they learned in the program in their further studies or at the workplace.

Additionally, 100% of respondents are either working or studying six months after completing the MSc. Additionally, several alumni have pursued further studies at top-ranking universities or remained at UCL to complete their PhD research. 

You can find out more about our graduate destinations on our ‘What do UCL graduates do?’ page.

Employability

We expect our graduates to become valuable contributors across science, technology and engineering sectors, in both industry and academia. This programme equips students with a strong blend of subject-specific and highly transferable skills valued by employers. These include professional software development, high-performance computing, numerical methods and optimisation, and advanced scientific modelling. These technical capabilities are complemented by strong communication, presentation and problem-solving skills. Graduates are well-prepared to contribute to research, innovation, and complex problem-solving, with a solid foundation for leadership roles and continued professional development in fast-moving scientific and technical environments.

Networking

Activities are organised throughout the year both within the MSc programme and with the related Centre for Doctoral Training in Data Intensive Science. Students are encouraged to participate in scientific seminars, for example, those run by the Centre for Doctoral Training in Data Intensive Science and the UCL Centre for Inverse Problems.

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. A major research project which includes an element of programming forms one-third of the course.

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.

For full-time students, typical contact hours are approximately 8-10 hours per week. This includes 3 lecture modules, each typically involving 2.5 contact hours per week, and additional contact with a project supervisor once every two weeks.

In addition to these scheduled lectures, seminars, workshops, and tutorials, full-time students are expected to dedicate the equivalent of a full-time job to self-directed study and completing coursework assignments.

During terms one and two, full-time students can expect between 8-10 contact hours per teaching week, delivered through a combination of lectures, seminars, workshops, critiques (crits), and tutorials. In term three and throughout the summer period, students focus on completing their dissertation research while meeting with their dissertation supervisors once every two weeks.

The research-project module is 60 credits, and consists of around 600 hours personal study time alongside approximately 15-20 hours contact time.

Contact hours and schedules may vary depending on individual module choices, pathway selections, and other programme-specific factors.

Modules

The programme is made up of modules to the value of 180 credits.  The programme consists of a research essay (30 credits), five optional core modules (75 credits) and one elective module (15 credits) or a dissertation/report (60 credits) plus either 6 optional core modules (90 credits) and two elective modules (30 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 1: Students should take three or four taught modules from among their choice of six or eight taught modules. These could be optional and elective modules.

Term 2: Students should take the remaining of their six or eight 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 2.

Term 3: 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 research essay (30 credits), five optional core modules (75 credits) and one elective module (15 credits) or a dissertation/report (60 credits) plus either six optional core modules (90 credits) and two elective modules (30 credits).

In Year 1: Students will take four (or more) taught modules from among their choice of six or eight taught modules. These could be optional and elective modules.

In Year 2: 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 1 or Year 2.

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.

Compulsory modules



Optional modules












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 are 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.

Placement

Some students may be able to take an industry group project.

Accessibility

The department will endeavour to make reasonable adjustments for students with disabilities, including those with long-term health conditions, neurodivergence, learning differences and mental health conditions. This list is not exhaustive. If you're unsure of your eligibility for reasonable adjustments at UCL, please contact Student Support and Wellbeing Services.

Reasonable adjustments are implemented on a case-by-case basis. With the student's consent, reasonable adjustments are considered by UCL Student Support and Wellbeing Services, and where required, in collaboration with the respective department.

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information about support available can be obtained from UCL Student Support and Wellbeing Services.

For more information about the department and accessibility arrangements for your course, please contact the department.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2026/27) £16,800 £8,400
Tuition fees (2026/27) £42,700 £21,350

Postgraduate Taught students benefit from a cohort guarantee, meaning that their tuition fees will not increase during the course of the programme, but UCL reserves the right to increase tuition fees to reflect any sums (including levies, taxes, or similar financial charges) that UCL is required to pay any governmental authority in connection with tuition fees.

The tuition fees shown are for the year indicated above. Where the course 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.

Additional costs

For full-time and part-time offer holders with a fee status classification of UK, a fee deposit will be charged at 2.5% of the first year fee.

For full-time and part-time offer holders with a fee status classification of Overseas, a fee deposit will be charged at 10% of the first year fee.

Further information can be found in the Tuition fee deposits section on this page: Tuition fees.

For students undertaking an optional placement or industry project, there may be a small token cost (typically under £50) to cover items such as a printed programme or entry fee. In many cases, these costs may be subsidised or covered by the department.

For those who wish to complete additional work from home when not on campus, it is recommended that students have access to a computer with above-average processing power, memory, and graphics capabilities. While a standard laptop may suffice for basic tasks, a high-performance laptop or desktop — featuring at least 16GB RAM, a multi-core processor, and dedicated graphics — is advised for optimal performance. 

Please note that personal equipment is recommended for convenience but is not mandatory, as all required tasks can be completed using the university's computer labs and resources.

For in-person teaching, UCL’s main teaching locations are in zones 1 (Bloomsbury) and zones 2/3 (UCL East). The cost of a monthly 18+ Oyster travel card for zones 1-2 is £119.90. This price was published by TfL in 2025. For more information on additional costs for prospective students and the cost of living in London, please view our estimated cost of essential expenditure at UCL's cost of living guide.

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.

See all the ways you can fund your studies

Next steps

There is an application processing fee for this course of £90 for online 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 scientific area you would like to purse a project in
  • 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 courses (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2026-2027

Apply for this course

Got questions? Get in touch

Physics and Astronomy
Physics and Astronomy

j.tennyson@ucl.ac.uk

UCL is regulated by the Office for Students.