Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less
Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic m ....Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic mutation in individual plants, providing an unprecedented level of detail into an important but understudied source of biological variation. By applying these methods to an iconic experimental population, This project aims to provide the first insights into the genome-wide causes and consequences of somatic mutation in plants.Read moreRead less
Smart comparison and assessment of prediction models for better health using next generation data mining. Prediction models can be used to provide early warning of events, such as adverse medical outcomes. This project will develop principles for the smart management of large collections of prediction models using data mining, enabling more timely medical interventions for Australians to live healthier and longer.
How the gut nervous system interacts with bacteria. This project aims to reveal how the enteric nervous system of the gastrointestinal (GI) tract interacts with the gut microbiota. Gut function has largely been studied without considering microbiota. The project will use genetically modified animal models, image analysis of gut motility and sequencing of gut microbes, and develop neurophysiological methods to understand gut function. Expected benefits include better understanding of mechanisms u ....How the gut nervous system interacts with bacteria. This project aims to reveal how the enteric nervous system of the gastrointestinal (GI) tract interacts with the gut microbiota. Gut function has largely been studied without considering microbiota. The project will use genetically modified animal models, image analysis of gut motility and sequencing of gut microbes, and develop neurophysiological methods to understand gut function. Expected benefits include better understanding of mechanisms underlying antibiotic resistance, risks associated with discretionary caesarean sections and the benefits of breastfeeding.Read moreRead less
Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high ....Bio-inspired Computing for Problems with Chance Constraints. Bio-inspired algorithms have successfully been applied to a wide range of optimisation problems. Uncertainties in real-world applications can lead to critical failures of production schedules or safe critical systems. Chance constraints model such uncertainties and allow to limit the possibility of such failures. This future fellowship builds up the area of bio-inspired computing for problems with chance constraints. It develops high performing bio-inspired algorithms for stochastic problems where the constraints can only be violated with a small probability. The outcomes will lead to more effective and reliable optimisation methods for complex planning processes in areas of national priority such as mining and manufacturing.Read moreRead less
Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an in ....Target detection: neural networks, behaviour and biomimetic applications. This project aims to understand the neural and behavioural mechanisms that allow insects to efficiently detect moving targets in visual clutter, despite being equipped with small brains and low-resolution eyes. The project is expected to generate fundamental knowledge using a unique combination of quantitative behaviour, neurophysiology, pharmacological intervention and biomimetic modelling. Expected outcomes include an increased understanding of neural mechanisms underlying sensory selectivity, the development of novel techniques, and enhanced capacity for interdisciplinary collaborations. The project will provide significant knowledge as the developed biomimetic algorithms should be applicable for increased performance in drones or other unmanned vehicles.Read moreRead less
Uncovering microRNA decay regulation in mammalian cells. MicroRNAs (miRNAs) constitute a novel mechanism used by cells to regulate gene expression, however, very little is known about the mechanisms affecting miRNA accumulation. Characterisation of the kinetics of miRNA turnover is of paramount importance to establish the reliability of miRNAs as novel biomarkers. This project aims to characterise miRNA stability in mammalian cells, investigate mechanisms of turnover and establish their importan ....Uncovering microRNA decay regulation in mammalian cells. MicroRNAs (miRNAs) constitute a novel mechanism used by cells to regulate gene expression, however, very little is known about the mechanisms affecting miRNA accumulation. Characterisation of the kinetics of miRNA turnover is of paramount importance to establish the reliability of miRNAs as novel biomarkers. This project aims to characterise miRNA stability in mammalian cells, investigate mechanisms of turnover and establish their importance on the regulatory function of miRNAs. Such information is critical in the future development of targeted therapeutics.Read moreRead less
Advanced Interface Technologies for Computational Science & Simulation. The project will research novel computer vision technologies that enable the next generation of visualisation portals for scientific collaboration. The development of new computer vision tools is key to truly natural human-machine interaction. The research outcomes of this project directly align with National Research Priority 3: Frontier Technologies. It supports four of the five relevant priority goals - Breakthrough Scien ....Advanced Interface Technologies for Computational Science & Simulation. The project will research novel computer vision technologies that enable the next generation of visualisation portals for scientific collaboration. The development of new computer vision tools is key to truly natural human-machine interaction. The research outcomes of this project directly align with National Research Priority 3: Frontier Technologies. It supports four of the five relevant priority goals - Breakthrough Science, Frontier Technologies, Smart Information Use, and Promoting an Innovation Culture and Economy. Outcomes of this research are also relevant to Research Priority 4: Safeguarding Australia, and has direct applications to video surveillance technology. Significant commercial opportunities, including licensing and spin-offs exist.Read moreRead less
Comparative Biogeography of Australasian biota. Establishing an internationally recognised biogeographical research program will help scientists, policy makers and the public understand the past and future distribution patterns of the plants and animals of Australia. Discovering these patterns will help conservation biologists and government implement the right policies and practices to deal with biodiversity loss and climate change.
Statistical Methods for Next Generation Genome-Wide Association Studies. This project aims to develop cutting-edge statistical methods to analyse large genomic datasets and identify genetic variants associated with inter-individual differences in various human traits. Knowledge of trait-associated DNA variants is instrumental in understanding how natural selection has shaped human traits. By integrating genomic data from diverse and underrepresented populations, this project further expects to c ....Statistical Methods for Next Generation Genome-Wide Association Studies. This project aims to develop cutting-edge statistical methods to analyse large genomic datasets and identify genetic variants associated with inter-individual differences in various human traits. Knowledge of trait-associated DNA variants is instrumental in understanding how natural selection has shaped human traits. By integrating genomic data from diverse and underrepresented populations, this project further expects to contribute to the equitable use of genomic technologies in humans, regardless of geographical origins. Expected outcomes of this research include novel analysis methods and software tools, which should broadly and significantly benefit gene discovery in other species, including those of agricultural relevance.Read moreRead less