MSc
MSc Scientific Computing and Data Analysis (Computer Vision and Robotics)
Using the latest scientific computing and data analysis techniques, explore some of the biggest research questions in computer vision and robotics and learn how autonomous cars and intelligent robots interact with the environment around them.
How to apply Apply via UCAS
Course details
Start date
Degree Type
MSc
Program Code
G5T509
Course length
1 year full-time
Typical offer
Tuition Fees
- Home (Full-time): £14,500 per year
- Overseas (Full-time): £34,000 per year
Overview
Developments in fields such robotics, 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 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 modelsImplementation and application of fundamental techniques in an area of specialisation (as well as Computer Vision and Robotics we offer options in Astrophysics, Earth and Environmental Sciences, or Financial Technology) The MISCADA specialist qualification in Computer Vision and Robotics is designed to equip you with the background knowledge and skills to address some of the biggest research questions in computer vision and robotics, such as how we can develop future mobility solutions which combine autonomy with safety and reliability. The course explores areas such as computer vision, machine learning, robotic motion and planning, as well as reinforcement learning. 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 computer vision and robotics, 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
G5T509
Course length
1 year full-time
Typical offer
Tuition Fees
- Home (Full-time): £14,500 per year
- Overseas (Full-time): £34,000 per year
What you'll study
Core modules
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Computer Vision
explores contemporary concepts, approaches and algorithms in computer vision and examines how current research is applied in the industry. Examples of themes include stereo vision, object tracking, real-time processing approaches, scene reconstruction from multiple image, object detection, and applications of computer vision for autonomous navigation
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Deep Learning for Computer Vision and Robotics
explores key concepts, approaches and algorithms for the use of deep machine learning and its application within industry. Examples of themes include scene reconstruction and understanding from multiple images, video or active sensing; simultaneous localisation and mapping (SLAM) from varying sensor inputs; visual odometry from varying sensor inputs; and robotic guidance and control.
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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.
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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 robotics, 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.
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Robotics – Planning and Motion
develops your knowledge of key concepts, approaches and algorithms in robotics, and how current research is applied in the industry. Examples of themes include robot classification, position and orientation, typical actuators/sensors and feedback control, simultaneous localisation and mapping (SLAM), and path planning and obstacle avoidance.
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 Engineering and Advanced AlgorithmsContinuous and Discrete Systems
Learning
This degree is organised by the Department of Computer Science in collaboration with the Department of Mathematical Sciences, the Department of Physics. 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 include group and individual presentations. In addition to access to your own small robotics kit, 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 computer vision and robotics field, or in close cooperation with our industrial partners.Entry requirements
Fees & Funding
Choose which fees you want to see:
Home / Island students
£14,500 per year
International / EU Students
£34,000 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.
