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Durham University


G5K609 Scientific Computing and Data Analysis MSc Postgraduate Taught  2019


Degree MSc
Mode of study Full Time
Duration 12 months
Location Durham City
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Department(s) Website

Course Summary


Advances in fields such as Physics, Engineering or Earth Sciences is increasingly driven by those most skilled in computational techniques. Notably, people skilled to write codes for the most powerful computers in the world and skilled to process the biggest data sets in the world make a difference.

The MSc Scientific Computing and Data Analysis is intended to provide Masters-level education in Computer Science aspects of scientific computing (algorithms, data structures, implementation techniques and computer tool usage), in Mathematical aspects of data analysis and application knowledge in the chosen specialisation domain.

The course is designed along five core educational aims:

  1. Train the next generation of research-affine data and computational scientists and engineers for the UK high tech sector; they have to be equipped with a very solid understanding of the underlying computing technologies and methodologies
  2. Equip you with the skills and knowledge to apply successfully for further higher education programmes (PhD) with a strong computing and data flavour in Durham or outstanding international institutions
  3. Provide you with the opportunity to obtain a deep insight into the state-of-the-art in the respective application domain with respect to computational and data challenges
  4. Enable you to bridge the widening gap between application domains, big data challenges and high-performance computing once you have mastered the course
  5. Make you aware of the societal, economical and ethical responsibilities, opportunities and implications tied to massive data processing and compute power; this includes training on entrepreneurship.

Course structure 

The course is structured into five modules spanning three terms and it is offered “with a specialisation in astrophysics” or “with a specialisation in particle physics”.

The course is designed such that:

  1. you will obtain a solid baseline in methodological skills
  2. you can either put emphasis on data analysis or scientific computing 
  3. you will do a challenging project either within the methodological academic departments (Mathematical Sciences or Computing Science), or within the specialisation area, or in close cooperation with our industrial partners
  4. you will acquire important professional skills spanning collaboration and project management, presentation and outreach as well we entrepreneurial thinking
  5. you will study selected topics from your specialisation area with a strong emphasis on computational and data challenges.

Course Learning and Teaching

The MSc uses a wide range of learning and teaching methods:

  • Lectures
  • Practical classes/computer labs
  • Independent study, research and analysis
  • Project (dissertation) and coursework
  • Group and individual presentations

A detailed list of learning and teaching methods is found per module in the module descriptions.

Besides the formal characteristics clarified in these descriptions, students from the course will be given the opportunity to work with a wide variety of top notch computer kit and software. This includes systems such as GPGPU/heterogeneous architectures (cmp Core IIB), HPC systems with specialist software installations (such as performance analysis tools; cmp Core I and Core IIB), GPU-based AI kit (Core IIA and Core IIB) and data acquisition tools (Core IIA). The course is strongly research-led and research-based.

Admissions Process

Subject requirements, level and grade

  • a UK first or upper second class honours degree (BSc) or equivalent
    • In Physics or a subject with basic physics courses OR
    • In Computer Science OR
    • In Mathematics OR
    • In any natural sciences with a strong quantitative element.

We strongly encourage students to sign up for a specialisation area they already have some background of affinity. At the moment, the course thus targets primarily Physics students.

  • Programming knowledge on a L3 level in at least one programming language and commitment to learn C and Python independently if not known before. See Additional requirements.

Additional requirements

The course page provides self-assessment tests and tutorial links to assess your programming skills. We expect applicants to confirm themselves that they are aware of the required programming skills and provide evidence (course transcripts, links to programming projects or brief description of conducted projects).

English Language requirements

Please check requirements for your subject and level of study.

How to apply

Fees and Funding

Full Time Fees

EU Student £9,600.00 per year
Home Student £9,600.00 per year
Island Student £9,600.00 per year
International non-EU Student £22,500.00 per year

The tuition fees shown are for one complete academic year of full time study, are set according to the academic year of entry, and remain the same throughout the duration of the programme for that cohort (unless otherwise stated).

Please also check costs for colleges and accommodation.

Scholarships and funding

Career Opportunities

Department of Computer Science

For further information on career options and employability, including the results of the Destination of Leavers survey, student and employer testimonials and details of work experience and study abroad opportunities, please visit our employability web pages

Open days and visits

Pre-application open day

Overseas Visit Schedule

Postgraduate Visits


Department Information

Department of Computer Science


The Department of Computer Science offers postgraduate courses that are challenging and technologically relevant, covering topics including big data, computer graphics, computer vision, image analysis, the Internet and the mathematical foundations of computing. You will have access to extensive and diverse research facilities, for example a Tier-3 supercomputer, a visualisation suite, several general-purpose computing on graphics processing units clusters and workstations, autonomous cars, and a team of intelligent robots. We have strong links with industrial partners; recent graduates have become successful entrepreneurs and software developers, have gained prestigious positions in banking and finance, and have entered the IT and engineering industries.


Ranked joint 1st in the UK for Internationally Excellent or World-Leading research impact in REF 2014.