Predictive Modelling and Scientific Computing (MSc/PGDip/PGCert/PGA) (2024 Entry)
Explore our Predictive Modelling and Scientific Computing taught Master’s degree.
Our Predictive Modelling and Scientific Computing MSc trains students in the theory and practical implementation of cutting-edge predictive modelling techniques, exposing them to established, as well as emerging, applications in science and engineering.
Course overview
Predictive Modelling is a fusion of mathematical modelling, machine learning and scientific computing, providing a powerful new way of thinking about how to model complex systems and improve technology and design.
Enhancements in computer processing power and access to ‘Big Data’ have led to a growth in the number of applications of predictive modelling into areas as diverse as environmental science, energy, healthcare, materials engineering, food science and geology. Our MSc in Predictive Modelling and Scientific Computing educates future specialists in computational science and engineering, equipping them to apply appropriate computational techniques to understand, define and develop solutions to a range of science and engineering problems, including those of national and global importance.
Core modules cover uncertainty quantification and predictive modelling, scientific computing and scientific machine learning, whilst the choice of three optional modules gives students the opportunity to specialise the application focus of the course to align with their interests. Students will participate in individual and group research projects, as well as writing reports and presenting technical work, thus developing the project management and numerical skills sought by employers.
The MSc can be studied part-time over two years to suit those in employment. PG Diploma, Certificate and Award options are also available for those who would like to take a subset of modules.
This course is running for the first time in 2023 and will equip graduates for further study in areas of critical science and technological importance, or for employment in a broad range of data-intensive industries where modelling, design and decision making under uncertainties is important. We have strong links with a range of potential employers.
General entry requirements
Minimum requirements
A minimum 2:1 undergraduate UK Honours degree or equivalent international qualification, in an engineering, physical sciences or mathematical subject.
You can see how your current degree score or GPA equates to the British system in our Study pages in the Equivalent scores table.
We are willing to consider applications from students with lower qualifications on a case-by-case basis, particularly when the applicant can evidence relevant employment, practical experience or strong performance in undergraduate modules related to their proposed postgraduate course of study.
To ensure you have the essential foundations for the course, and depending on your overall academic profile, we may require you to take a mathematical skills test.
English language requirements
You can find out more about our English language requirementsLink opens in a new window. This course requires the following:
You can find out more about our English language requirements. This course requires the following:
- Band A
- IELTS overall score of 6.5, minimum component scores not below 6.0
International qualifications
We welcome applications from students with other internationally recognised qualifications.
For more information, please visit the international entry requirements pageLink opens in a new window.
Additional requirements
Candidates with professional experience should include their CV with their application.
Core modules
Fundamentals of Predictive Modelling (ES98A) (15 credit)
This module provides students with fundamental knowledge for predictive modelling and uncertainty quantification. It gives an overview of the essential elements of the mathematical, statistical, and computational techniques needed to provide well-calibrated predictions for the behaviour of physical systems.
Numerical Algorithms and Optimisation (MA934) (15 credit)
This module provides students with knowledge (and practice) of important numerical optimisation concepts at the intersection between mathematics and scientific computing. Algorithmic structures, data structures, numerical method construction and performance assessment will form key parts of the module, with applications and use cases concentrated on topics in linear algebra, signal processing and optimisation.
Scientific Machine Learning (ES98E) (15 credit)
This module provides students with knowledge in the modern field of scientific machine learning, which is a fusion of scientific computing and machine learning. Students will learn how to use a variety of statistical and machine learning techniques to train models which combine data-driven and mechanistic models and assess their ability to make useful predictions.
Predictive Modelling Group Project (ES98B) (30 credit)
Predictive modelling group project with training in key professional and research skills and collaborative writing. Groups of students will create a complex piece of predictive modelling research software using methods and design principles introduced in previous modules in the course.
Individual Research Project (ES98C) (60 credit)
Each student will conduct significant and novel research as an individual project, and present the background and findings in the form of a dissertation. The research question must address some aspect of modelling, resulting in new knowledge, methodology or understanding, accompanied by uncertainty quantification.
Optional modules
The selection of optional modules is likely to include:
- Modelling and Computation of Fluid Dynamics Across Phases and Scales (MA9M4)*
- Particle-based Modelling (ES98D)*
- Modelling and Simulation of Engineering Materials (ES98F)*
- Mathematical and Computer Modelling (ED4C3)
- Quantum Chemistry (PX919)
- High Performance Computing (PX457)
- Advanced Topics in Fluids (MA4L0)
- Monte Carlo Methods (ST407)
- Advanced Topics in Data Science (ST419)
- Statistical Learning and Big Data (ST420)
- Continuum Mechanics (MA6J1)
- Advanced Computational Chemistry (CH413)
- Data Mining (CS909)
- Biomolecular Simulation (PX923)
*Please note that students are required to take at least one of these three optional modules.
PG Diploma, Certificate and Award options are also available for those who would like to take a subset of modules. More information
Teaching
Core modules cover uncertainty quantification and predictive modelling, scientific computing and scientific machine learning, whilst the choice of three optional modules gives students the opportunity to specialise the application focus of the course to align with their interests. Students will have the opportunity to participate in individual and group research projects, as well as to write reports and present technical work, thus developing the project management and numerical skills sought by employers.
Class sizes
Class sizes for lectures, practical laboratory sessions and seminars vary depending on the number of students taking the module.
Typical contact hours
The MSc degree (totalling 180 credits) comprises:
- One group project with skills training module (30 credits)
- 6 taught modules (15 credits each)
- A research project (60 credits)
The typical workload for a 15-credit module is as follows:
- 20-30 hours of lectures/seminars
- 10-15 hours of supervised computer lab work
- 50 hours of private/directed study
- 60 hours of assessed work
The research project is valued at 60 credits and students should plan to execute around 600 hours of work towards the completion of the project dissertation.
Assessment
A combination of coursework and written examinations.
Your timetable
Your personalised timetable will be complete when you are registered for all modules, compulsory and optional, and you have been allocated to your lectures, seminars and other small group classes. Your compulsory modules will be registered for you and you will be able to choose your optional modules when you join us.
Careers and employability
This course was new for entry in 2023 and equips graduates for further study in areas of critical science and technological importance, or for employment in a broad range of data-intensive industries where modelling, design and decision making under uncertainties is important. We have strong links with a range of potential employers.
Our department has a dedicated professionally qualified Senior Careers Consultant offering impartial advice and guidance together with workshops and events throughout the year. Previous examples of workshops and events include:
- Options in Engineering
- Meet an Engineer
- Engineering, Science and Technology Fair
- Considering a PhD in the STEM Subjects
- Warwick careers fairs throughout the year
Engineering at Warwick
Use your maths and science skills to creatively solve real-life problems.
Find out more about us on our website.Link opens in a new window
Our Postgraduate Taught courses
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- Diagnostics. Data and Digital Health MSc
- Diagnostics, Data and Digital Health (Medical Diagnostics) MSc
- Diagnostics, Data and Digital Health (Medical Imaging) MSc
- Electrical and Electronic Engineering (MSc)
- Electrical Power Engineering (MSc)
- Humanitarian Engineering (MSc/PGDip/PGCert/PGA)
- Humanitarian Engineering (with Management) (MSc)
- Humanitarian Engineering (with Sustainability) (MSc)
- Predictive Modelling and Scientific Computing (MSc)
Our Postgraduate Research courses
Tuition fees
Tuition fees are payable for each year of your course at the start of the academic year, or at the start of your course, if later. Academic fees cover the cost of tuition, examinations and registration and some student amenities.
Fee Status Guidance
We carry out an initial fee status assessment based on the information you provide in your application. Students will be classified as Home or Overseas fee status. Your fee status determines tuition fees, and what financial support and scholarships may be available. If you receive an offer, your fee status will be clearly stated alongside the tuition fee information.
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If you believe that your fee status has been classified incorrectly, you can complete a fee status assessment questionnaire. Please follow the instructions in your offer information and provide the documents needed to reassess your status.
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Additional course costs
As well as tuition fees and living expenses, some courses may require you to cover the cost of field trips or costs associated with travel abroad.
For departmental specific costs, please see the Modules tab on the course web page for the list of core and optional core modules with hyperlinks to our Module Catalogue (please visit the Department’s website if the Module Catalogue hyperlinks are not provided).
Associated costs can be found on the Study tab for each module listed in the Module Catalogue (please note most of the module content applies to 2022/23 year of study). Information about module department specific costs should be considered in conjunction with the more general costs below:
- Core text books
- Printer credits *
- Dissertation binding *
- Robe hire for your degree ceremony
* - Dissertations and Assignments are only submitted digitally. However students may wish to print and bind their dissertation for their own purposes. Students on some courses will have a final poster presentation as part of their project and the printing of posters will be at the students’ expense.
Scholarships and bursaries
Scholarships and financial support
Find out about the different funding routes available, including; postgraduate loans, scholarships, fee awards and academic department bursaries.
Living costs
Find out more about the cost of living as a postgraduate student at the University of Warwick.
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How to apply
Applications are now open for courses that start in September and October 2025.
Applications will close on 2 August 2025 for students who require a visa to study in the UK, to allow time to receive a CAS and complete the visa application process.
How to apply for a full-time postgraduate taught course in WMG
Please note, places are often limited, so we recommend that you submit your application as early as possible. Please check our department webpages for more specific information.
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