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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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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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lead to a PhD position at SPMS in NTU Singapore (based on performance). Key Responsibilities: Contribute to the development of algorithms Develop codebase in Python and perform large-scale simulations
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candidates will be required to fund the difference between the home fees and international fees. Overview Are you interested in developing Brain-Computer Interface technologies to control brain stimulation in
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This project develops quantum-AI tools to optimise urban hydroponic food systems and evaluate their therapeutic impact on student well-being. The expected outcome is to create quantum-reinforced AI
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Technology Centre (MTC). You will push the limits of multiphysics CFD for laser manufacturing by developing a next-generation simulation capability for laser drilling - with relevance to additive
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: Develops advanced Agro-geoinformatic algorithms for monitoring and predicting the conditions of crop, pasture, and their environment with advanced remote sensing and geospatial technologies; Develops and
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solutions using first motion. Experience in full waveform inversion using innovative tools (e.g. ISOLA) and methods (ML), earthquake location algorithms, computer programming and geophysical equipment
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functional theory. In collaboration with Phasecraft, a leading quantum algorithms company, this project will explore the generation of new quantum computing datasets and the development of machine learning
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into learning architectures. Collaborating with experimental research groups, enabling real-world validation and application of newly developed algorithms.