New parameter inference for stochastic models of tissue growth

My research group is recruiting a PhD student who will work on a project to produce and apply new computational methods for parameter estimation with a focus on discrete models that describe tissue growth experiments. Funding is provided through an Australian Research Council Discovery Project grant, both domestic and international applicants are welcome.

Mathematical models of tissue growth experiments are important tools that can be used to provide insight into both fundamental biological processes as well as experimental design for experiments that produce tissues grown on 3D-printed scaffolds. New high-resolution experimental data reveals individual cellular-scale details that can be modelled with stochastic individual-based models. The PhD project will develop new and efficient methods for parameter inference for these stochastic models, paying particular attention to parameter identifiability, parameter inference and data-informed model prediction.

The successful applicants will be based in the School of Mathematical Sciences at QUT as a part of my research group.

Applications: Applicants should hold a research Masters degree or equivalent (e.g. first-class Honours degree degree) in applied mathematics, physics, engineering or related discipline. Strong academic performance, excellent written and spoken communication skills, and expertise in computational techniques (e.g. Julia, C++, FORTRAN) are essential.

The applicant must be eligible to enrol in a PhD at QUT. The annual stipend, $33,637 in 2024, is tax exempt for full-time students, and will support living costs for up to three years. International students will receive an accompanying QUT Higher Degree Research Tuition Fee Sponsorship.

Contact: For further information please contact Professor Matthew Simpson via e-mail [Email Address Removed] or twitter @profmjsimpson