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Australian State/Territory : ACT
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Research Topic : Computer simulation
Field of Research : Optimisation
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  • Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0346878

    Funder
    Australian Research Council
    Funding Amount
    $190,000.00
    Summary
    GeoWulf: An Inference Engine for Complex Earth Systems. The project is to build a `Beowulf' cluster as a platform for solving complex data inference problems in the Earth sciences, and in particular the fields of thermochronology, seismology, crustal and mantle dynamics, and landform evolution. A Beowulf cluster is a network-linked set of commonly available `off-the-shelf' PC-computers configured to give unprecedented performance/cost ratio. Projects using the Beowulf facility will combine .... GeoWulf: An Inference Engine for Complex Earth Systems. The project is to build a `Beowulf' cluster as a platform for solving complex data inference problems in the Earth sciences, and in particular the fields of thermochronology, seismology, crustal and mantle dynamics, and landform evolution. A Beowulf cluster is a network-linked set of commonly available `off-the-shelf' PC-computers configured to give unprecedented performance/cost ratio. Projects using the Beowulf facility will combine state-of-the-art computational techniques recently developed at ANU, and high quality data sets collected over the past decade to address fundamental questions in the Geosciences.
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    Funded Activity

    Research Networks - Grant ID: RN0459979

    Funder
    Australian Research Council
    Funding Amount
    $2,250,000.00
    Summary
    ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this te .... ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing. Sensor networks, a collection of diverse sensors interconnected via an ad-hoc communication network, are identified as one of the key technologies that over the next two decades will change the way we live. This research network brings together an interdisciplinary team of outstanding Australian researchers representing all the key disciplines required to successfully deploy sensor networks and links this team with the foremost international authorities and leading industry players in the area of sensor networks. This research network will guide collaborative research that will ensure Australia to play a world leading role in sensor network development and implementation.
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    Funded Activity

    Discovery Projects - Grant ID: DP0774054

    Funder
    Australian Research Council
    Funding Amount
    $263,993.00
    Summary
    Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a .... Unifying Modern Approaches in Machine Learning. The proposed research will lead to better algorithms for some important machine learning problems that could lead to better tools for extracting useful knowledge from data such as in bioinformatics and sensor networks; it will strengthen an international collaboration with one of the world's top centres of machine learning research; it will contribute to an open source toolkit of machine learning algorithms which will put Australia on the map as a provider of sophisticated machine learning software; it will provide training opportunities for several PhD students and a postdoc to work with some of the best machine learning researchers in the world.
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