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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 this scholarship you must: Have a first-class Honours degree in Computer Science or equivalent Have strong computational, programming, algorithms, and data analysis skills Provide evidence of adequate oral and
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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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ADM+S invites applications for PhD scholarships from students interested in the following areas: The development and distribution of automated decision-making (ADM) systems The applications
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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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vehicles capture videos or images for underwater pipes for inspection purposes. However, highly blurry or poor-quality videos can only be received under noisy environment. Therefore, developing accurate
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population