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Research Topic : Medical Devices
Field of Research : Optical Physics
Australian State/Territory : SA
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  • Funded Activity

    Super Science Fellowships - Grant ID: FS100100039

    Funder
    Australian Research Council
    Funding Amount
    $835,200.00
    Summary
    Disruptive approaches to biological sensing. Optical fibre-based biosensors have the potential to transform our ability to monitor our environment, protect our nation's assets and safeguard our citizens, and to offer improved clinical diagnostics and food quality control by creating tools that can detect biomolecules in real-time within complex samples. To fulfil this mission, we propose to develop new fibre-based sensing architectures for sensing biomolecules that have the potential to be sensi .... Disruptive approaches to biological sensing. Optical fibre-based biosensors have the potential to transform our ability to monitor our environment, protect our nation's assets and safeguard our citizens, and to offer improved clinical diagnostics and food quality control by creating tools that can detect biomolecules in real-time within complex samples. To fulfil this mission, we propose to develop new fibre-based sensing architectures for sensing biomolecules that have the potential to be sensitive, selective, fast and compact.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT200100154

    Funder
    Australian Research Council
    Funding Amount
    $778,452.00
    Summary
    Next generation photonic waveguide sensors enabled by machine learning. This project aims to establish the next frontier in photonic waveguide sensing, by using machine learning to shift the complexity out of conventional photonic-waveguide/optical-fibre sensors and into smart detection algorithms. The complexity and instability of multimode photonic waveguides, traditionally a hinderance to sensing, will be advantageously employed to train deep learning models for sensing. Expected outcomes inc .... Next generation photonic waveguide sensors enabled by machine learning. This project aims to establish the next frontier in photonic waveguide sensing, by using machine learning to shift the complexity out of conventional photonic-waveguide/optical-fibre sensors and into smart detection algorithms. The complexity and instability of multimode photonic waveguides, traditionally a hinderance to sensing, will be advantageously employed to train deep learning models for sensing. Expected outcomes include the creation of intelligent photonic sensors that can, in principle, measure any environmental parameter using any optical waveguide material. It will create new critically needed measurement capabilities for challenging harsh environments, such as extreme temperature and in-vivo biochemical sensing.
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    Funded Activity

    Super Science Fellowships - Grant ID: FS110200009

    Funder
    Australian Research Council
    Funding Amount
    $835,200.00
    Summary
    Transformational diagnostics. Australia has established world-leading capabilities in optical fibres and surface science that, when brought together, have the potential to transform applications that require non-invasive, real-time and/or portable biological detection tools. We propose a novel and ambitious suite of projects that bring together these capabilities with experts in reproductive health, forensics and explosives to solve pressing problems in each of these areas that have the promise .... Transformational diagnostics. Australia has established world-leading capabilities in optical fibres and surface science that, when brought together, have the potential to transform applications that require non-invasive, real-time and/or portable biological detection tools. We propose a novel and ambitious suite of projects that bring together these capabilities with experts in reproductive health, forensics and explosives to solve pressing problems in each of these areas that have the promise to develop into new industries for Australia as well as to explore rich science opportunities at the boundaries of these disciplines.
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    Showing 1-3 of 3 Funded Activites

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