Industrial Transformation Training Centres - Grant ID: IC190100031
Funder
Australian Research Council
Funding Amount
$3,973,202.00
Summary
ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understand ....ARC Training Centre in Data Analytics for Resources and Environments (DARE). Understanding the cumulative impact of actions regarding the use of our resources has important long-term consequences for Australia’s economic, societal and environmental health. Yet despite the importance of these cumulative impacts, and the availability of data, many decisions and policies are based on limited amounts of data and rudimentary data analysis, with little appreciation of the critical role that understanding and quantifying uncertainty plays in the process. The aim of Data Analytics in Resources and Environment (DARE) is to develop and deliver the data science skills and tools for Australia’s resource industries to make the best possible evidence-based decisions in exploiting and stewarding the nation’s natural resources.Read moreRead less
Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project ....Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project aims to develop novel and effective algorithmic techniques and statistical methods for a class of branching processes with dependences. We will use these results to study significant problems in the conservation of endangered island bird populations in Oceania, and to help inform their conservation management.Read moreRead less
Empirical and computational solutions for multi-omics single-cell assays. Emerging single-cell sequencing technologies are transforming molecular cell biology, but identifying novel cell types and their functions requires the integration of highly heterogeneous data. The development of computational methods able to extract biologically relevant results is hindered by the lack of high-quality datasets. This project aims to develop novel sequencing methodologies and generate data to drive our dime ....Empirical and computational solutions for multi-omics single-cell assays. Emerging single-cell sequencing technologies are transforming molecular cell biology, but identifying novel cell types and their functions requires the integration of highly heterogeneous data. The development of computational methods able to extract biologically relevant results is hindered by the lack of high-quality datasets. This project aims to develop novel sequencing methodologies and generate data to drive our dimension reduction multivariate method developments for data integration. By combining in silico and in vivo approaches, the project is anticipated to benefit scientists willing to work in cutting-edge single-cell research by providing useful protocols and tools to generate novel insights in cell biology. Read moreRead less