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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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(UNSW), Prof. Brendan McKay (ANU) and Prof. Ian Wanless (Monash). The project aims to develop new theoretical tools to address fundamental challenges about graphs and hypergraphs with given degrees
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as required. Demonstrated high level of written and oral communication skills. Preferable Experience in eukaryotic cell culture/tissue culture Expertise with advanced graphing and/or data analysis
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. Demonstrated high level of written and oral communication skills. Preferable Experience in eukaryotic cell culture/tissue culture Expertise with advanced graphing and/or data analysis software (Prism, Origin Pro
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and synthesis of new materials. You should have a PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical
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group to work on a project developing provable network security methods that use higher-order graph-based abstractions to model networks and network security problems. Scalable algorithms developed
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Multi-modal Machine Learning—including areas like Neuro-symbolic AI, Knowledge Graphs, Contextual AI, Conversational AI, and Trustworthy & Safe AI. This role also offers the opportunity to explore human
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, and publish high-impact research. Engage with industry and government, contributing to governance and promoting inclusion and diversity. About you PhD qualification in Computer Science, Data Science
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The proposed PhD project aims to build a machine learning/deep learning-based decision support system that provides recommendations on precision medicine for paediatric brain cancer patients based
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the Division of Research and Innovation as part of the co-investment from the University of Adelaide. This program will support ten full-time PhD students commencing studies from 2025 to 2027. In 2025, we