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Scientific Computing and Data Analysis (Astrophysics) at Durham University - UCAS

Durham University

Degree level: Postgraduate

Scientific Computing and Data Analysis (Astrophysics) (Taught)

Course options

2024 - 20252025 - 2026
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Open days

21Oct
Durham University - Postgraduate Online Open Week
Postgraduate
27Nov
Durham University - Postgraduate Open Day
Postgraduate
10Feb
Durham University - Postgraduate Online Open Week
Postgraduate

Course summary

Developments in many areas of science and engineering are increasingly driven by experts in computational techniques. Those with the skills to write code for the most powerful computers in the world and to process the biggest data sets in the world can truly make a difference. Our suite of Masters in Scientific Computing and Data Analysis (MISCADA) offers an application-focused course to deliver these skills with three interwoven strands:

  • Computer Science underpinnings of scientific computing (algorithms, data structures, implementation techniques, and computer tool usage)
  • Mathematical aspects of data analysis and the simulation and analysis of mathematical models
  • Implementation and application of fundamental techniques in an area of specialisation (as well as Astrophysics we offer options in Computer Vision and Robotics, Earth and Environmental Sciences, or Financial Technology)
The MISCADA specialist qualification in Astrophysics is designed to equip you with the background knowledge and skills to address some of the biggest research questions in fundamental science, such as how we can use large surveys and supercomputer simulations to probe the nature of dark matter and dark energy. The course explores areas such as stellar structure and evolution, galaxy formation, large-scale structure and simulations of structure formation. You can find out more here. There’s great synergy between the modules and you will be given plenty of opportunities to put your learning into practice from the start of the course. Our research-led approach allows you to take some of the newest theoretical ideas and directly translate them into working codes in their respective application areas. If you have an undergraduate degree in a science subject with a strong quantitative element, including computer science and mathematics and want to work at the highest level in astrophysics, either in academia or in industry, then this could be the course you’re looking for. Core modules Introduction to Machine Learning and Statistics provides knowledge and understanding of the fundamental ideas and techniques in the application of data analysis, statistics and machine learning to scientific data. Introduction to Scientific and High Performance Computing provides knowledge and understanding of paradigms, fundamental ideas and trends in High Performance Computing (HPC) and methods of numerical simulation. Professional Skills delivers C refresher training with an outlook into large-scale code usage. You will also develop wider professional skills in areas such as entrepreneurship, intellectual property and build the skill you will need to communicate novel ideas in science and reflect on the ethical issues around data and research. The Project is a substantive piece of research into an unfamiliar area of astrophysics, scientific computing or data analysis, or a related area in cooperation with an industry partner. The project will develop your research, analysis and report-writing skills. Astrophysics teaches you state-of-the-art research and science across a broad range of astrophysics topics, from stellar populations to galaxy formation and high-energy astrophysics. This module introduces the basic research skills needed for postgraduate research.

Modules

In recent years optional modules have included: Advanced Statistical and Machine Learning: Foundations and Unsupervised Learning; Advanced Statistics and Machine Learning: Regression and Classification; Data Acquisition and Image Processing; Performance Modelling, Vectorisation and GPU Programming; Advanced Algorithms and Discrete Systems; Computational Linear Algebra and Continuous Systems.

Assessment method

Assessment takes a combination of forms including coursework, presentations and a project which is worth one-third of your total mark. You will complete your dissertation-style project on a topic of your choice from within the methodological academic departments (Mathematical Sciences or Computer Science), or within the astrophysics field, or in close cooperation with our industrial partners.

How to apply

International applicants

If you are an international student who does not meet the requirements for direct entry to this degree, you may be eligible to take a pre-Masters pathway programme at the Durham University International Study Centre.

This course has a subject classification which requires students whose nationality is outside the European Economic Area (EEA) or Switzerland to have an ATAS certificate, irrespective of country of residence at the point of application.

Further information can be found on the UK Government's website: www.gov.uk/academic-technology-approval-scheme

Entry requirements

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 Earth Sciences OR In Engineering OR In any natural sciences with a strong quantitative element.

English language requirements

Durham University welcomes applications from all students irrespective of background. We encourage the recruitment of academically well-qualified and highly motivated students, who are non-native speakers of English, whose full potential can be realised with a limited amount of English Language training either prior to entry or through pre-sessional and/or in-sessional courses. It is the normal expectation that candidates for admission should be able to demonstrate satisfactory English proficiency before the start of a programme of study, whether via the submission of an appropriate English language qualification or by attendance on an appropriate pre-sessional course. Acceptable evidence and levels required can be viewed by following the link provided.

English language requirements

https://www.durham.ac.uk/study/international/entry-requirements/english-language-requirements/

Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

The tuition fees for 2025/26 academic year have not yet been finalised, they will be displayed on the www.durham.ac.uk/study website once approved.

Sponsorship information

For further information see the course listing on the Durham University website.

Scientific Computing and Data Analysis (Astrophysics) at Durham University - UCAS