Research in the field of mathematical biology from the Faculty of Science, University of Melbourne.
David Balding Application of mathematical, statistical and computational methods in genetics (population, evolutional, medical and forensic genetics) and related areas of biology.
Douglas Brumley Using microfluidic devices, fluorescent microscopy and high speed imaging in conjunction with mathematical models to investigate fundamental physical principles.
Pengxing Cao Applied mathematics, mathematical biology.
Yaoban Chan Statistics and mathematical biology.
Edmund Crampin Modelling heart cells to understand the development of heart disease, interactions between cells and nanoparticles, and computational approaches to study the network of genetic interactions underlying cancer.
Jennifer Flegg Using mathematical biology to study wound healing, tumour growth and epidemiology.
Roslyn Hickson Mathematical modelling of infectious diseases, particularly malaria in the Asia-Pacific region.
John Holmes Statistics, statistical genetics.
Barry Hughes Applied mathematical methods, probability modelling, mathematical biology, continuum modelling, random walks, random environments.
Stephen Leslie Statistical genomics, including detecting and controlling for population differences in genetic data, typing complex genetic variation, and statistical analyses of the relationship of genetic variants to disease.
James McCaw Modelling of host-pathogen-drug dynamics with a focus on influenza and malaria, to develop public health control strategies for emerging and re-emerging infectious diseases.
James Osborne Numerical and computational methods for mathematical models of biological phenomena.
Guoqi Qian Statistics theory, biostatistics, bioinformatics, computational statistics and mathematical methods for climatology, ecology and the environment.
John Sader Plasticity and elasticity, dynamic force spectroscopy, nanocrystal mechanics, atomic force microscopy, continuum modelling, colloidal interactions.
Heejung Shim Data science, Bayesian statistics, computational biology, statistical genomics, stochastic processes, machine learning, applied statistics.
Michael Stumpf The inference of mathematical models using statistical inference and machine learning approaches.
Agne Tilunaite Mathematical medicine.
Damjan Vukcevic Biostatistical research with a specialisation in statistical genetics.
Melbourne Integrative Genomics (MIG)
We aim to understand biological systems, with a focus on genomes as the blueprint for each system. We are interested in biological systems of different scales.
Mathematical Research Institute MATRIX
MATRIX is an international research institute that runs research programs where world lead researchers in the mathematical sciences, as well as experts from business and industry, can come together.