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Equation learning for partial differential equation models of stochastic random walk models

Random walk models are often used to represent the motion of biological cells. These models are convenient because they allow us to capture randomness and variability. However, these approaches can be computationally demanding for large populations.One way to overcome the computational limitation of using random walk models is to take a continuum limit description, which can efficiently provide insight into the underlying transport phenomena.While many continuum limit descriptions for homogeneous random walk models are available, continuum limit descriptions for heterogeneous …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Mathematical Sciences

New mathematical and computational techniques for partial differential equations in heterogeneous media

Mathematical models involving both partial differential equations (PDEs) and heterogeneous media are useful for simulating many important physical processes. This includes:groundwater flowpollutant transportheat transferdrug deliverytumour growth.This project focuses on developing new mathematical and computational techniques to solve, simulate and/or analyse PDEs in heterogeneous media.

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Mathematical Sciences

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