Scientific Computing and Data Analysis (Astrophysics)

Program Overview

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Scientific Computing and Data Analysis (Astrophysics)

Overview

Using the latest scientific computing and data analysis techniques, explore the fascinating field of astrophysics and address some of the biggest research questions in fundamental science.

Start Dates

• September 2025

Degree Type

• MSc

Course Length

• 1 year full-time

Location

• Durham City

Programme Code

• G5T309

Course Details

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.

Course Structure

Year 1 Modules

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.

Optional Modules:

• 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

Learning

This degree is jointly organised by the Department of Computer Science with specialisations offered in collaboration with the Department of Mathematical Sciences, the Department of Physics and the Department of Earth Sciences. Teaching and learning methods are varied, they include a combination of lectures, practical classes/computer labs, independent study, research and analysis, a project (dissertation) and coursework. Some modules also include group and individual presentations.

You will also be given the opportunity to work with a wide variety of high-quality computer kit and software. This includes HPC systems such as GPU clusters, systems with heterogeneous architectures and specialist software installations (such as performance analysis tools), AI tools and data acquisition tools.

Assessment

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.

Entry Requirements

All streams require 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.

We encourage applicants to select a specialization area that aligns with their background. Please note that standard business degrees do not provide the necessary mathematical foundation.

Additional Requirements

• Applicants must demonstrate strong programming skills in at least one compiled language, preferably C or C++, although Rust, Java, C#, Fortran, or Pascal are also acceptable. Proficiency in Python may suffice if the applicant has a strong background in their chosen specialization. Those lacking experience in C or C++ are advised to enrol in our pre-sessional course.
• Additionally we require knowledge of undergraduate-level mathematics, covering linear algebra, calculus, integration, ordinary and partial differential equations, and probability theory.
• Please see the University guidance for information on required English language levels.

Fees and Funding

Full Time Fees

• Home students: £14,500 per year
• EU students: £34,000 per year
• Island students: £14,500 per year
• International students: £34,000 per year

The tuition fees shown are for one complete academic year of study and are set according to the academic year of entry. Fees will be subject to an annual inflationary increase and are expected to rise throughout the programme of study.

Career Opportunities

Qualifications in computer science are highly sought after by employers across the globe and an award from our Department provides the academic skills, industry insight and research-informed approach that sets postgraduates up for careers in a broad range of sectors.

Many postgraduates have gone on to work as software engineers, analysts, consultants, programmers and developers. Some have founded their own start-ups or work in leading software companies, high-technology consultancies, banking and finance, retail, engineering, the communications and IT industry.

Department Information

Computer Science

The Department of Computer Science’s academic fusion of technology and independent thinking places it firmly at the cutting edge of computer learning. We bring innovative applications together with critical thought processes to give you the skills to play a key role in the data-led future.

The Department is at the heart of the fast-paced world of applications and algorithms. We maintain an in-depth understanding of the fundamentals of computation and are fully up to speed with the latest technologies that emerge at an ever-increasing rate.

Learning from academics who lead cutting-edge research provides valuable insight into high quality projects, and gives our postgraduate community the opportunity to play a role in shaping a future in which crucial developments in society are supported by technological innovation.

Taught courses balance fundamental knowledge and an emphasis on programming and mathematical skills with practical applications. The content and structure are such that they suit postgraduates who already have experience in the industry or other employment and want to add a formal qualification to their achievements.

Researchers in the Department offer a range of expertise across the computer science spectrum in areas such as artificial intelligence, data science, bioinformatics, high-performance computing, graphics and fundamental algorithms.

We ensure our research-led activity does not function in isolation and keep close links with local high-technology industries as well as national and international employers. Those relationships ensure we are at the leading edge of developments across the sector and can revise and adapt the Department’s curriculum to reflect the changes.

Facilities

The Department is located in a £40 million purpose-built building in the heart of Durham at Upper Mountjoy and features open-plan work areas, breakout spaces for collaboration projects, laboratories and computer rooms.

We are fortunate to have supercomputers for High-Performance Computing and for data analysis and machine learning as well as access to several visualisation and data postprocessing laboratories.

We are also able to host local computer hardware which give postgraduate researchers a safe environment to test prototype solutions, explore innovative technologies they are developing or to actually design new solutions.

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