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Australian State/Territory : WA
Research Topic : Adaptive Immunity
Australian State/Territory : ACT
Status : Closed
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  • Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models: The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object .... Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models: The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics.
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    Funded Activity

    Arbovirus Activation And Modulation Of NLRP3 Inflammasome

    Funder
    National Health and Medical Research Council
    Funding Amount
    $779,720.00
    Summary
    This project aims to establish how mosquito borne viruses such as Ross River and dengue viruses interacts with the human host to cause disease, including how the virus evades the host’s immune response to persist and cause disease for prolonged periods. Knowing how differences in the virus and the host’s immune system interplay to cause asymptomatic to severely disabling disease will assist in devising new treatments and prevention programs to lessen the impact of these diseases in Australia.
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    Funded Activity

    Spatio-temporal Dynamics Of Arbovirus Infection

    Funder
    National Health and Medical Research Council
    Funding Amount
    $491,504.00
    Summary
    Mosquito-borne alphaviruses such as Ross River and chikungunya viruses cause widespread epidemics and exert extreme pressure on the public health systems of affected regions. Alphaviruses spreads to joints and triggers a severe disease in those affected. There are no effective treatments or vaccines. The project will investigate virus-host interaction at the bite site. The outcome will be new knowledge to treat infection at the mosquito bite site to prevent joint disease.
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    Funded Activity

    Novel Insights Into The Pathobiology Of Alphavirus Infections

    Funder
    National Health and Medical Research Council
    Funding Amount
    $827,660.00
    Summary
    Infections with mosquito-borne viruses are increasing at an alarming rate worldwide. Ross River virus is endemic in parts of Australia, PNG and Pacific islands, while chikungunya virus is distributed globally and causes recurrent pandemics that involve millions of people. These viruses cause severe musculoskeletal disease for several months after infection. This project aims to establish how these viruses interact with the human host to cause disease and may provide a basis for new treatments.
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    Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100203

    Funder
    Australian Research Council
    Funding Amount
    $385,000.00
    Summary
    Autonomous benthic observing system. This project seeks to improve our ability to monitor marine habitats and characterise their variability by enhancing the Integrated Marine Observing system (IMOS) Autonomous Underwater Vehicle (AUV) Facility. The new AUV infrastructure will reduce operating costs, increase robustness of the sampling effort and insure continued operation for the next decade.
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    Showing 1-5 of 5 Funded Activites

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