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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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, electronic, robotic and software engineering skills to develop and evaluate machine vision-based algorithms for automated plant care in a controlled environment with artificial lighting. Relevant tasks will
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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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implement machine learning algorithms for complex data analysis. Utilise advanced programming skills (Python, MATLAB, C) and image processing libraries to develop computational solutions. Publish research
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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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automated recovery algorithms, improving system resilience. Research Areas for Master’s and PhD Students AI-Enhanced Resource Forecasting and Optimization: Research Focus: Developing and testing ML algorithms
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fixed-term appointment Remuneration: 4-year scholarship package totalling approximately $47,000 per annum tax exempt (2025 rate) 4-year Project Expense and Development package of $13,000 per annum
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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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- WorkspaceFull-timeDigital SolutionsNathan, Queensland Manager, Partnership Development (Quantum)Full-timeDVC ResearchSouthport, QLD Manager, Partnership Development (Quantum)Full-timeDVC ResearchNathan, QLD
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domains for applications to the mining industry and beyond. We have an opportunity for a passionate and skilled research scientist to design and develop cutting-edge algorithms and fused sensor systems