Mathematical modelling is becoming an important tool in science, engineering, economics, business and society in general, due to the rise of computer power and data availability. In this major you will learn the mathematical techniques that are essential for model development, application and assessment including computational and numerical skills. These techniques include ordinary and partial differential equations, which use ideas from calculus, and stochastic modelling, which uses ideas from probability theory.
In this major we use Python as the computational platform. This powerful software is rapidly becoming industry standard and will enable you to solve and manipulate models so that you get to grips with model outputs. You will have opportunities to apply mathematical modelling techniques in biology, medical sciences, physics and chemistry and engineering applications.
To ensure success, make sure you are aware of the required level of mathematics (assumed knowledge) for this curriculum component. Visit the mathematics learning support webpage, to understand your pathway to success, including the sequence of units you should complete and the support services available.
When you complete this major you will have the mathematical modelling and computational foundations to build a career in research (Universities, CSIRO), the public sector (Bureau of Meteorology, state and federal government agencies), or the private sector (engineering, consulting, IT, finance).
Requirements for completion of a major or minor in Mathematical Modelling and Computation are listed in the Mathematical Modelling and Computation unit of study table.
Website: School of Mathematics and Statistics
Email: maths.schooloffice@sydney.edu.au
Prof. Martin Wechselberger
Email: martin.wechselberger@sydney.edu.au
