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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 25 days ago
candidate will develop independent and collaborative research in the area of Machine Learning, Natural Language Processing, and Algorithm Design, and work in a diverse cross-disciplinary team with researchers
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developed and implemented such methods for a plethora of non-classical logics [2]. But how can we guarantee that the implementation is faithful to the theory? Indeed, how can we be sure that we have not made
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data infrastructure necessary for collaborative research into, and development of, analytical techniques and algorithmic models. The Faculty of Information Technology has a mission to advance social good
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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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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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or Research Fellow to contribute to groundbreaking quantum algorithms research led by Dr Riddhi Gupta and Associate Professor Sally Shrapnel. You’ll work at the forefront of theory, simulation and
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, scalable numerical algorithms for extracting the evolution model of the relevant dynamical skeleton, quantifying associated uncertainties. We will develop mathematical theory underpinning the novel
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disease patients using radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical
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radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical imaging. Within our research
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algorithms for computing MML solutions beyond the one-dimensional case. Extend existing dynamic programming approaches to higher-dimensional problems or develop novel approximation methods that preserve