MSc/PGDip/PGCert Predictive Modelling and Scientific Computing

  • DeadlineStudy Details:

    Full time: 1 year (MSc), 9 months (PGDip, PGCert) Part time: 2 years (MSc), 18 months (PGDip, PGCert)

Masters Degree Description

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, building on students’ existing programming skills and 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.

Entry Requirements

A minimum 2:1 undergraduate UK Honours degree or equivalent international qualification, in an engineering, physical sciences or mathematical subject.

Please note that applicants will need post A2 Level (or equivalent) knowledge in Mathematics, covering topics such as linear algebra, calculus and analysis, including differential equations, as well as probability and statistics. This could be gained through mathematics modules taken as part of an undergraduate course. It is expected that candidates have a good understanding of these topics at the start of their MSc studies.

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Fees

For fees and funding options, please visit website to find out more

Programme Funding

We offer a variety of postgraduate funding options for study at the University of Warwick, from postgraduate loans, university scholarships, fee awards, to academic department bursaries.

Student Destinations

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.

Module Details

Core modules

  • Fundamentals of Predictive Modelling
  • Numerical Algorithms and Optimisation
  • Scientific Machine Learning
  • Predictive Modelling Group Project
  • Individual Research Project 

Optional modules

Previously, a selection of the following options has been offered:

  • Modelling and Computation of Fluid Dynamics Across Phases and Scales *
  • Particle-based Modelling *
  • Predictive Modelling of Advanced Engineering Materials*
  • High Performance Computing
  • Statistical Learning and Big Data
  • Advanced Topics in Fluids
  • Advanced Computational Chemistry
  • Biomolecular Simulation
  • Biomedical Systems Modelling

*Please note that students are required to take at least one of these three optional modules.

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