Industrial Transformation Research Hubs - Grant ID: IH130200012
Funder
Australian Research Council
Funding Amount
$2,748,358.00
Summary
ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). This Research Hub aims to undertake simultaneous modelling of deep Earth and surface processes, spanning basin scales to individual sediment grains. The Hub will develop and apply cutting-edge basin simulation approaches to transform the seeding and testing of basin exploration models, extending their viability to complex, ....ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). ARC Research Hub for Basin GEodyNamics and Evolution of SedImentary Systems (GENESIS). This Research Hub aims to undertake simultaneous modelling of deep Earth and surface processes, spanning basin scales to individual sediment grains. The Hub will develop and apply cutting-edge basin simulation approaches to transform the seeding and testing of basin exploration models, extending their viability to complex, inaccessible remote and deep exploration targets. The Hub will fuse multidimensional data into five dimensional basin models (space and time, with uncertainty estimates) by coupling the evolution of mantle flow, crustal deformation, erosion and sedimentary processes, achieving a quantum leap in basin modelling and petroleum systems analysis.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC180100030
Funder
Australian Research Council
Funding Amount
$3,925,357.00
Summary
ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching ....ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching objectives are to enable development and adoption of new practices to improve productivity and asset reliability for industry and to foster a new maintenance technology service sector for national and international markets.Read moreRead less
Hierarchical information processing in the primate visual cortex. This project aims to understand how visual information is transformed across hierarchical levels in the brain. Neuroscientists have long recognised that the visual cortex can be conceptualised as a hierarchical processing network. This became apparent when learning algorithms based on hierarchical networks ("deep learning") changed artificial intelligence. This project will combine high-throughput electrophysiology with analytical ....Hierarchical information processing in the primate visual cortex. This project aims to understand how visual information is transformed across hierarchical levels in the brain. Neuroscientists have long recognised that the visual cortex can be conceptualised as a hierarchical processing network. This became apparent when learning algorithms based on hierarchical networks ("deep learning") changed artificial intelligence. This project will combine high-throughput electrophysiology with analytical tools adopted from deep learning. By explaining the physiological properties of higher-level neurons in terms of hierarchical networks, the project expects to address long standing questions in neuroscience, and provide insights on biological hierarchical computation.Read moreRead less