This person does not currently hold a position at QUT.


Dr Sam Clifford
Discipline *
+61 7 3138 2863
View location details (QUT staff and student access only)
Identifiers and profiles
ORCID iD LinkedIn

PhD (Queensland University of Technology), Bachelor of Applied Science (Honours) Mathematics (Queensland University of Technology)

* Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008


Dr Clifford’s PhD thesis, conferred in 2013, was completed within the International Laboratory for Air Quality and Health (QUT) under the supervision of Professor Lidia Morawska, Professor Kerrie Mengersen and Dr Sama Low Choy. The topic of the thesis was “Spatio-temporal modelling of ultrafine particle number concentration”.   His undergraduate background is in computational mathematics, mathematical modelling and applied physics. He holds a B AppSc (Mathematics) with Honours for his thesis on numerical analysis of shear-augmented flow, under the supervision of Dr Glenn Fulford and Dr Timothy Moroney.   Dr Clifford blogs about his teaching and research at

Dr Clifford works on a variety of environmental statistical challenges, including reef coral cover, jaguar conservation, and air pollution and its health impacts.





This information has been contributed by Dr Sam Clifford.


Dr Clifford is the unit coordinator and lecturer for SEB113 – Quantitative Methods in Science, a first year unit in the Bachelor of Science. The unit equips students with knowledge and skills in data visualisation, linear algebra, calculus, and statistical modelling through problem based learning and case studies from the sciences. In 2015 the SEB113 teaching team, led by Dr Clifford, was awarded a Vice-Chancellor’s Performance Award for their work redesigning the unit. Dr Clifford’s interests in teaching include introducing first year students to mathematical and statistical modelling as a creative exercise, the use of the R software to create reproducible analyses and effective visualisations, and ensuring students are aware of the level of mathematics and statistics required to study science such as the development of a diagnostic tool for all incoming Bachelor of Science students to help guide them towards an appropriate mathematics unit for their first semester of study.

This information has been contributed by Dr Sam Clifford.


For publications by this staff member, visit QUT ePrints, the University's research repository.