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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind
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defence algorithms are remain a challenge in the research community. Furthermore, most existing AML algorithms can only apply to Euclidean space. How to extend existing AML algorithms to non-Euclidean and
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This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation
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Seizure prediction algorithms will be developed using the one-of-a-kind ultra-long-term human intracranial EEG dataset obtained from the Neurovista Corporation clinical trial of their Seizure
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, identifying molecular disease signatures and matching them with the most effective therapeutic interventions are essential. The Hudson‐Monash Paediatric Precision Medicine (HMPPM) Program aims to develop and
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approximation algorithms for deriving dual bound within a branch-and-bound algorithms. Other directions could use Machine Learning or new decompositions. This subject is generally quite open so it is important to
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/C++) computer codes implementing a cryptographic algorithm. Although desired, background in advanced cryptography is not a must. Application of a PET algorithm to solve a real-life problem: This
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of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed
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science conference [1]; one of our papers is recognised as Clarivate Web of Science HighCite (top 1% of papers for the field of research) [2]; three of our algorithms (TS-Chief, InceptionTime and Rocket
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cooperating with each other, but in many cases competing for individual gains. This structure may not always work for the benefit of science. The purpose of this project is to use game theory and computational