PhD Project: Deep Time Global Scale Landscape Evolution Models
The University of Sydney
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Since the ’90s, numerical models have been designed to estimate long-term catchment dynamic, drainage evolution as well as sedimentary basins formation in response to various mechanisms such as tectonic or climatic forcing. These models rely on a set of mathematical and physical expressions that simulate sediment erosion, transport and deposition. These numerical simulations can reproduce the first order complexity of Earth’s surface geomorphological evolution.
Recently, our group has developed a new global scale model of landscape, sediment routing and stratigraphy to evaluate the evolution of Earth surface and its interaction with the atmosphere, the hydrosphere, the tectonic and mantle dynamics. Our open-source code can be used to better characterise many aspects of the Earth system ranging from the role of atmospheric circulation on physical denudation, from the influence of mantle convection on erosion and deposition of sediments, from the location and abundance of natural resources to the evolution of life.
This project is part of an Industry-funded grant and aims to simulate source-to-sink systems at global scale using the new numerical tool Gospl. It will consist in building new functionalities within the code and analysing models’ outputs under different geological scenarios. In collaboration with supervisors and industry partners, the candidate will be in charge of:
- classical modelling activities (parameterisation/calibration/validation) with applications to specific continental margins,
- improvement of numerical solutions to either increase the performance of the existing code or to build new functionalities, and
- development of interactive workflows to ease quantitative comparisons between simulation results and complex geo-Earth datasets.
The candidate will need to have a master’s degree in Geosciences, Computer Sciences or related fields. Strong curiosity in the project’s topic and strong interest in modelling and its combination with field data (experience in modelling and programming are of advantage). In addition, the candidate will be interacting with our Industry partners and will have the opportunity to work with data scientists from the Sydney Informatics Hub (SIH). The SIH will offer courses on programming in Python, covering relevant know-how for the project, and provide broad, transferable skills for industry, government organisations or academia after the completion of the PhD.
You have a master’s degree in Geosciences, Computer Sciences or related fields. Strong curiosity in the project’s topic and strong interest in modelling and its combination with field data (experience in modelling and programming are of advantage). In addition, you will be interacting with our Industry partners and will have the opportunity to work with data scientists from the Sydney Informatics Hub (SIH). The SIH will offer courses on programming in Python, covering relevant know-how for the project, and provide broad, transferable skills for industry, government organisations or academia after the completion of the PhD.
- be willing to conduct research into quantitative landscape modelling and stratigraphic evolution,
- hold an honours degree (first class or second class upper) in geosciences, mathematics or computer sciences or a related field, or a master’s degree in a related field with a substantial research component.
You will join a dynamic team of Earth scientists at the University of Sydney. We have a recognised track record in community software development, open-access data sets and virtual Earth modelling. We foster cross-disciplinary collaboration across a range of interests and research areas in Australia and overseas. Opportunities to attend national and international conferences are encouraged to disseminate scientific research and collaborate with researchers and industry partners.
Application deadline for the fully funded PhD position is September 28, 2021.
Your application consists of three steps:
- Online registration & submission of application documents (June 30 – September 28, 2021)
- Phone or video conference interview (until October 10, 2021),
- Recruitment (end-October, 2021)
Find out more and apply online: