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Research Associate/Research Fellow in Complex Systems Applied to Industrial Maintenance - University of Western Australia

The Australian Centre for Transforming Maintenance through Data Science (CTMTDS) is a joint collaboration between Curtin University, the University of Western Australia and CSIRO, and industry partners Alcoa, BHP, and Roy Hill, as well as CORE Innovation Hub and the Minerals Research Institute of Western Australia. The Centre, co-funded by the Australian Research Council through the Industrial Transformation Training Centre scheme, aims to train a new generation of data scientist , equipping them with the skills needed to develop new data science methods for solving complex modelling, technical language processing and optimisation challenges in asset maintenance. This cohort of data scientists will drive an exciting transformation of maintenance practice in the Australian resources industry based on new advances in machine learning, artificial intelligence and optimisation. The Centre involves a team of 20 scientists and engineers at the three research institutes together with practicing engineers at the industry partners.

As a Research Associate/Research Fellow in the Department of Mathematics and Statistics you will have the rare opportunity to collaborate with a multidisciplinary team of academics in CTMTDS to conduct research leading to both industry impacts and high-quality publications.

Drawing on your strong research and practical skills you will develop algorithms and methods to support application of complex systems and network science to problems related to industrial maintenance . Applications will include knowledge graphs extracted from maintenance work orders, and cascading failures in complex engineering systems. You will engage with the Centre’s industry partners to identify and address maintenance-related industry questions using appropriate methods.

The role will complement existing areas of expertise in natural language processing, network science, dynamical systems and nonlinear time series analysis. You will also have the opportunity to mentor research students during study and industry placement as well as supporting and co-supervising final year undergraduate and PhD students.

Duration/PeriodTwo years
Deadline07/10/2022 0:00
Keywordsnonlinear time series analysis; complex networks; maintenance;

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