Experience

This pages details my education, academic, and teaching experience. For an overview of my industry and volunteering experience, please see my Linkedin profile.

Education

• Master of Philosophy (Applied Mathematics), 2024, The University of Adelaide, Australia.
  Dissertation title: Computable Characterisations of Uncertainty in Differential Equations.

• Bachelor of Mathematical Sciences (Advanced), 2021, The University of Adelaide, Australia.

Teaching

In April of 2024, I undertook a three-week teaching visit to the Ocean University of China, in the lovely city of Qingdao. This opportunity was part of Haide College, a joint initiative between the University of Adelaide and the Ocean University of China. I was involved with the delivery of two courses:

• Computational Bayesian Statistics, a fourth year course covering Bayesian modelling approaches with an emphasis on computational techniques.

• Data Science, a third year course covering the mathematical formulation and implementation of modelling approaches in data science.

During my time at the University of Adelaide, I had the opportunity to work casually within the School of Computer and Mathematical Sciences as a tutor and marker for a range of undergraduate courses. I have tutored the following courses:

• Decision Science PG: A postgraduate course covering simulation techniques in the support of decision making.
• Fluid Mechanics III: A third-year course covering fluid dynamics, including the derivation of physical laws and practical simulation methods.
• Modelling with Ordinary Differential Equations III: A third-year course covering ordinary differential equations and their formulation, numerical solution, analysis, and application to a range of business and scientific settings.
• Partial Differential Equations and Waves III: A third-year course covering partial differential equations, including formulation, analytical and numerical solutions, and interpretation.
• Professional Practice III: A professional development course for third-year computer science and mathematics students, in which I worked closely with my students to develop their job application, interview, teamwork, and communication skills.
• Statistical Modelling & Inference II: A second-year course covering statistical methods, including estimation, hypothesis esting, linear models, and maximum likelihood methods.
• Mathematics IM, IA, and IB: A set of introductory first-year courses to calculus and linear algebra, taken by all mathematics and engineering students.

Here are a few pieces of anonymous student feedback on my teaching, as surveyed each semester:

“Liam genuinely cares. His tutorials actively encourage student participation as we work through problems together, with him providing intuitive explanations to help in understanding not only the processes, but the physical interpretation and a general understanding of the underlying principles. His assignment feedback is well thought out and at times quite detailed, showing genuine effort to give helpful and constructive feedback. He has been a highlight of the course throughout the semester”

“Very engaging and was very approachable. Tried to make the course more interesting with his charisma.”

“Liam creates an interactive and engaging environment in tutorials. I appreciate his personal experiences and opinions that he shares, to make the content more applicable. Liam also provides really kind and constructive feedback.”

“Liam was one of the best teachers I’ve had at the university. He was very clear in his explanations of course material and often delivered concepts in particularly ‘down–to–earth’ terms that made them easier to understand.”

I have additionally been a marker/grader for the following courses:

• Decision Science PG
• Fluid Mechanics III
• Modelling with Ordinary Differential Equations III
• Partial Differential Equations and Waves III.
• Professional Practice III
• Differential Equations for Engineers II
• Multivariable and Complex Calculus II
• Statistical Modelling & Inference II
• Statistical and Numerical Methods II
• Mathematics IA and IB