MSc
MSc Scientific Computing and Data Analysis (Environmental and Geographic Information Systems)
Using the latest scientific computing and data analysis techniques, learn to predict and analyse aspects of climate change, the risks and hazards of the environment, and the exploitation of natural resources.
How to apply Apply via UCAS
Course details
Start date
Degree Type
MSc
Program Code
G5T909
Course length
1 year full-time
Typical offer
Tuition Fees
- Home (Full-time): per year
- Overseas (Full-time): per year
Overview
Developments in fields such physics, engineering, Earth sciences or finance 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 have the potential to make a positive impact on issues relating to the Earth and its environment. 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 modelsImplementation and application of fundamental techniques in an area of specialisation (as well as Earth and Environmental Sciences we offer options in Astrophysics, Computer Vision and Robotics, or Financial Technology) The MISCADA specialist qualification in Environmental and Geographic Information Systems is designed to equip you with advanced knowledge and skills in the use of sophisticated datasets and tools to tackle cutting-edge and societally-relevant problems relating to the Earth’s environment and management of its scarce resources. We introduce a variety of Earth and environmental datasets, as well as the specialist mathematical and software tools required for their quantitative and computational analysis. 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, including analysis of data across a range that includes satellites and handheld devices. 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 earth and environmental sciences, either in academia or in industry, then this could be the course you’re looking for.
Course details
Start date
Degree Type
MSc
Program Code
G5T909
Course length
1 year full-time
Typical offer
Tuition Fees
- Home (Full-time): per year
- Overseas (Full-time): per year
What you'll study
Core modules
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Earth and Environmental Sciences
introduces a variety of Earth and environmental, and geospatial datasets and the specialist mathematical and software tools required for their quantitative and computational analysis. The module also provides advanced knowledge of how to use these datasets and tools to tackle cutting-edge and societally-relevant problems. The module includes a field trip in which students can gather geospatial data and learn how to process it on the fly. The module culminates in a mini project.
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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.
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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 provides 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 ethical issues around data and research.
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Project
The is a substantive piece of research into an unfamiliar area of Earth and environmental sciences, 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.
Optional modules
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Plus optional modules which may include:
Advanced Statistical and Machine Learning: Foundations and Unsupervised LearningAdvanced Statistics and Machine Learning: Regression and ClassificationData Acquisition and Image ProcessingPerformance Modelling, Vectorisation and GPU ProgrammingAdvanced Algorithms and Discrete SystemsComputational Linear Algebra and Continuous Systems
Learning
This degree is organised by the Department of Computer Science with specialisations offered in collaboration with the Department of Earth Sciences, the Department of Mathematical Sciences, the Business School and the Department of Physics. Teaching and learning methods are varied, they include a combination of lectures, practical classes/computer labs, field work, 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 Earth and environmental sciences, or in close cooperation with our industrial partners.Entry requirements
Fees & Funding
Choose which fees you want to see:
Home / Island students
per year
International / EU Students
per year
Home / Island students
Part Time - per year
International / EU Students
Part Time - per year
The tuition fees shown are for one complete academic year of 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).
Find out moreDepartment Information
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Top 10
in the Complete University Guide 202511th
in the Guardian University Guide 2025Joint 6th
for student employability in the Complete University Guide 2025The 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. For more information see our department pages.
Read moreFacilities
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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State of the art building
Our new building features academic offices, offices for research staff and students, open-plan space for students to work, breakout spaces to collaborate, labs, computer rooms and, of course, a café.
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High-Performance Computing Cluster
Durham hosts its own local supercomputers (the Hamilton family) and the DiRAC Cosma machine.
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NVIDIA CUDA Centre (NCC)
This cluster is multifunctional in that it supports all aspects of research and teaching. Students (both masters and PhD) are able to access this cluster for running novel ML studies.
Find out more -
Career Opportunities
Employability
More Information
Our postgraduates leave with excellent career prospects and go on to diverse careers in academia, business and industry.
