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to contemporary challenges while mentoring the next generation of leaders. Building on its strong foundation in Optics and Photonics, EECS is expanding its research into quantum algorithms and their industrial
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, or spatial relationships of objects—and to indicate when it is unsure about its input. Key expected outcomes include the creation of monitoring algorithms that identify early signs of performance issues, and
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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and innovation catalyst, in this exciting project, you will develop novel algorithms to monitor and analyse workers' movements, detect harmful movement patterns, and implement simple intervention
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the appointment, and will have experience in asymptotic, algorithmic or probabilistic combinatorics, or a closely-related area. Applicants should also be active researchers with good written and oral
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Project (Next-Generation Solvers for Complex Microwave Engineering Problems). This project aims to design and develop physics-guided, data-driven algorithms that can accurately solve complex microwave
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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
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original research in asymptotic, algorithmic and/or probabilistic combinatorics, with particular focus on hypergraphs. Collaborate on research problems with the project team (Prof. Greenhill, Dr Isaev, A
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algorithms formulating industrial problems to make them accessible to quantum algorithms mapping quantum algorithms to specific use cases and applications optimizing algorithms in the context of such use cases
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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