/MSc Scientific Computing and Data Analysis (MISCADA)

IoC Partner

Provided by: Durham University

Course Area: North East

Course Code: G5K609

Course Type: Masters (taught)

Start date: 20211005

End date: 20220731

Subjects: Computer Science, Data Analytics, Data Science

Price: Over £10,000

Delivery Method: Face to face

Course overview

Advances in fields such as Physics, Engineering, and Earth Sciences are increasingly driven by those most skilled in computational techniques: people writing code for the most powerful computers in the world and analysing the biggest datasets in the world make a difference to science and, ultimately, to society.


The MSc in Scientific Computing and Data Analysis intends to provide postgraduate education in computer science aspects of scientific computing (algorithms, data structures, implementation techniques and computer tool usage), mathematical aspects of data analysis (statistics, machine learning), and application knowledge in the chosen specialisation domain (currently astrophysics and particle physics).


Goals of the Course

Our students will be exposed to a broad set of computational and data analysis techniques in the first term. In term 2 their studies will focus either on advanced data analysis or scientific computing and HPC. We train highly-skilled, technology-savvy specialists in a challenging course.


Our students will be trained to international research level in a specialisation area of their choice (currently astrophysics or particle physics) and will be in a position to contribute to the respective area. Our research-based and research-oriented education empowers our students to make a difference in the chosen application field, while the freedom to select from one of two core flavours plus one of two specialisations allows students to tailor the curriculum towards their needs and interest.


Our students will have a well-developed set of transferable skills. They will have experience of collaboration in teams and of communicating their science to different audiences. They will be exposed to entrepreneurial thinking and will have developed their personal take on the ethics of large-scale data and computing. We train the next generation of socially responsible scientists and engineers

Who is this course for

We strongly encourage students to sign up for a specialisation area they already have some background of affinity. At the moment, the course targets primarily Physics students. If you do not have a Physics degree, we strongly recommend you to contact the University beforehand to clarify whether you bring along the right background.


Programming knowledge on a L3 level in at least one programming language and commitment to learning C and Python independently if not known before.


Interest in Computational Physics or its Data Analysis. The course tackles computational and data analysis challenges from this area.

What will I learn

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:


  • you will obtain a solid baseline in methodological skills
  • you can either put emphasis on data analysis or scientific computing
  • 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
  • you will acquire important professional skills spanning collaboration and project management, presentation and outreach as well we entrepreneurial thinking
  • you will study selected topics from your specialisation area with a strong emphasis on computational and data challenges.
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