Overview
As part of this programme, students will actively participate in research projects that place a strong emphasis on computational aspects. These projects encompass a diverse range of captivating topics, all of which are relevant to real world applications, including but not limited to:
- Simulation of Granular Flow and Growing Sand-piles
- Finite Element Discretisation of Ordinary and partial differential equations
- Domain Decomposition
- Computational Spectral Theory
- Mathematical Modelling of Micro-electron Mechanical Systems
By honing your computational skills through this programme, you will be well-positioned to take advantage of the many exciting career opportunities available. The programme provides cutting-edge knowledge and practical experience to help students transition successfully into professional roles involving large-scale simulations, modelling, and machine learning models.
Your Student Experience
Our expertise
Within our MSc in Computational Mathematics and Data Analysis, our academics bring a wealth of expertise to enhance your educational journey. Their research and teaching intersect the realms of computational and applied mathematics, including:
- Data Science for Healthcare: Leveraging data analytics, machine learning, and statistical methods to advance medical diagnostics, treatment planning, and healthcare efficiency.
- Financial Modelling: Applying mathematical and computational techniques to analyse financial markets, risk assessment, and investment strategies.
- Artificial Intelligence in Robotics: Exploring the convergence of AI and robotics to develop innovative automation and autonomous systems, from self-driving vehicles to industrial automation.
Your learning environment
With MSc in Computational Mathematics and Data Analysis you'll excel in an exceptional learning environment:
- The National Robotarium: The National Robotarium is a world-leading centre for Robotics and Artificial Intelligence, creating innovative solutions to global challenges. Pioneering research moves rapidly from laboratory to market, developing skilled visionaries and delivering substantial benefits for society
- Innovation Hubs: As a student, you'll have access to data-driven innovation hubs like the GRID, home of the HW Maths Gym. The GRID offers exceptional opportunities to engage with fellow students, academics and cutting-edge technologies.
- Departmental Expertise: Heriot-Watt's Department of Mathematics has been excellent in applied and computational mathematics for over four decades. Our programmes sharpen your mathematical skills and apply them to real-world challenges, including those in sustainable finance.
- Research Excellence: In the recent Research Excellence Framework (REF2021), we ranked first in Scotland and 3rd in UK for Mathematical Sciences research.
Programme Structure
Mandatory September
- Modelling and Tools
Optional September
- Optimisation
- Modelling and Simulation in the Life Sciences
- Numerical ODEs
- Statistical Methods
- Data Assimilation
- Numerical Analysis (PDEs)
- Artificial Intelligence
Optional January
- Partial Differential Equations
- Bayesian Inference & Computational Methods
Mandatory May
Masters Project and Dissertation
Audience
Our master's programme is designed to equip students with the skills needed to conduct effective computer simulations for a wide range of practical mathematical, physical, chemical, and industry-related problems.
Key information
Duration
- Full-time
- 12 months
Start dates & application deadlines
- StartingApply anytime.
Language
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Delivered
Campus Location
- Edinburgh, United Kingdom
Disciplines
Computational Mathematics Data Analytics View 243 other Masters in Data Analytics in United KingdomWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
Entry is aimed at graduates with strong mathematical knowledge and skills. A 2:1 honours degree in mathematics, statistics or a related subject with a substantial mathematical content is desired.
We will accept 2:2 with relevant academic subjects and relevant professional qualifications.
Motivation and a willingness to work hard are also important pre-requisites.
Tuition Fees
-
International Applies to you
Applies to youNon-residents20456 GBP / year≈ 20456 GBP / year -
Domestic Applies to you
Applies to youCitizens or residents10864 GBP / year≈ 10864 GBP / year
Living costs
Edinburgh
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
Postgraduate scholarships and bursaries
We aim to encourage well-qualified, ambitious students to study with us and we offer a wide variety of scholarships and bursaries to achieve this. Over £6 million worth of opportunities are available in fee and stipend scholarships, and more than 400 students benefit from this support.In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Master's scholarship opportunities for Computational Mathematics and Data Analysis.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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