Dynamic Earth models, landscape dynamics, and basin evolution in the Phanerozoic


This project is designed to understand the interconnections between mantle dynamics, plate tectonics, paleogeography, basin evolution, and continental shelves. The project will investigate the spatial and temporal relationship between key tectonic events and landscape evolution (erosion and sedimentation), paleogeography (shoreline evolution), basin dynamics (subsidence and uplift) and mantle processes (dynamic topography). We will consider numerical forward modelling from a Bayesian perspective, providing a framework for robust model development of complex, non-linear Earth systems.  The project is designed to achieve a transformation in how we carry out continental-scale landscape evolution and basin modelling using modern data science and machine learning methods. Uncertainties in optimised models will be computed based on present-day and time-dependent data (paleocoastlines, exhumation history, sediment provenance).  These models will enable “synthetic geophysical profiling” (synthetic gravity, seismic profiles across basins) to underpin decision-making for future resource exploration and management. Additional supervisors are Tristan Salles (School of Geosciences) and Rohitash Chandra (Centre for Translational Data Science – CTDS). Research Location: School of Geosciences and Centre for Translational Data Science


Professor Dietmar Muller, Dr Tristan Salles, Dr Rohitash Chandra

Research Location

School of Geosciences

Program Type



The project is part of the ARC Basin Genesis Hub, a joint Australian Research Council-industry funded research centre.  The Hub is a showcase of connecting “Big Data” analysis and high-performance computing in an open innovation framework. The hub is fusing multidimensional data into 5D basin models (space and time, with uncertainty estimates) by coupling the evolution of mantle flow, crustal deformation, erosion and sedimentary processes using open-source modelling tools. See here for more details:


Additional Information

 The project will be carried out as a collaboration between the EarthByte Group in the School of Geosciences and the Centre for Translational Data Science/Sydney Informatics Hub.  See here for more information: 


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Tectonics, geodynamics, marine geology and geophysics, sedimentology, Machine learning, Bayesian optimisation, high-performance computing

Opportunity ID

The opportunity ID for this research opportunity is: 2254

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