Industrial Transformation Training Centres - Grant ID: IC170100030
Funder
Australian Research Council
Funding Amount
$4,133,659.00
Summary
ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students ....ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students and postdoctoral researchers. These researchers will lead the medical technology industry into a new era of data-driven personalised and precision medical devices and applications. The Centre will result in the development of capabilities in the core technologies of machine learning and the practical application of cognitive computing in the area of health.Read moreRead less
Building a visual world: how brain circuits create and use representations. This project aims to demonstrate the presence, computation, and use of an invariant representation for texture structure. The proposed approach is interdisciplinary and combines image analysis, electrophysiology, optogenetics and computational modelling.
Expected outcomes of this project include learning how neurons encode properties of natural images, defining a novel computational tool for analysis of textures, and ne ....Building a visual world: how brain circuits create and use representations. This project aims to demonstrate the presence, computation, and use of an invariant representation for texture structure. The proposed approach is interdisciplinary and combines image analysis, electrophysiology, optogenetics and computational modelling.
Expected outcomes of this project include learning how neurons encode properties of natural images, defining a novel computational tool for analysis of textures, and new knowledge of how multiple brain areas work together to represent the visual world. This should provide significant benefits for the development of artificial visual systems, and impact on brain research broadly by increasing the number of tools available to predict complex representations at the cellular level.Read moreRead less