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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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solutions across teaching and research. The role involves designing and programming embedded systems, developing software interfaces, and providing support for a wide range of equipment and systems used in
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fabrication facilities as well as high performance computing (HPC) facilities at QUT. PhD2: Pore-network modelling of reactive transport As a PhD student, you will develop efficient pore-network modelling
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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for government, defence and commercial. The aim of this project is to develop, implement and evaluate prototypes of practical quantum-resistant (aka post-quantum) algorithms for enhancing the security of a Senetas
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computer vision and machine learning methods and adapt new algorithms to automate inspection procedures of PV plants. Given the data captured by a remotely operated drone, we first investigate the required
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, and evaluation of advanced software engineering techniques and methodologies aimed at detecting, mitigating, and preventing misinformation online. The successful candidate will develop novel AI-driven
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with