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Research Topic : Software
Scheme : ARC Future Fellowships
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  • Funded Activity

    ARC Future Fellowships - Grant ID: FT120100291

    Funder
    Australian Research Council
    Funding Amount
    $813,902.00
    Summary
    Controlling ultracold atomic gases. This project will develop ways to control the quantum state of ultracold atomic gases. These experimentally accessible systems will be used to investigate and understand a huge range of scientific phenomena from stars to superconductors, and enable critical quantum technologies that will revolutionise communications and precision measurement.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT150100330

    Funder
    Australian Research Council
    Funding Amount
    $931,552.00
    Summary
    The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molec .... The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molecular atlas projects have successfully revealed rules of genome output and regulation, by mining patterns that are evident across multiple cell types and datasets. By applying this philosophy to relevant, well-curated stem cell experiments, this project aims to create new methods for the integration and interrogation of smaller individual datasets. These methods should have broad utility and enable new avenues in tissue engineering.
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