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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
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-of-the-art facilities at Adelaide Microscopy, including multiple transmission electron microscopes (TEM) such as a Glacios 200 kV Cryo-TEM. Additionally, resources available include the Phoenix high
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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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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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, 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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brings together an industry partner, a university and Australia’s leading science agency, CSIRO, to co-develop a four-year industry-focused PhD project. The program supports a three-way partnership aiming
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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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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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in lower vertebrates, if it is present in sharks and how or if cartilage repair occurs in lower vertebrates. This project aims to develop a better understanding of the biology of cartilage in lower
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to establish similar tools in the US, Canada, UK, New Zealand, Hong Kong, Argentina and Fiji. It was developed by Hunter New England Local Health District and won Research Australia’s prestigious data innovation