577 systems-science "https:" "https:" "https:" "https:" "U.S" uni jobs at Monash University
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integral to maintaining assessment integrity while contributing to efficient, error-free operations across the assessment lifecycle. This position will be responsible for delivering expert quality assurance
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Maxwell King PhD Scholarship The Maxwell King Scholarship (MKS) is named after Professor Maxwell King, who has made an outstanding contribution to graduate research at Monash University, including
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available
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This project is similar in flavour to the Conscious AI project but rather than come from a Philosophical/Neuroscience/Math/Theory angle, this project aims to build self-aware neural networks
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Project Background and Motivation The "inverse design" of molecules from analytical spectra (such as MS2, NMR, or IR) is a fundamental bottleneck in analytical chemistry, metabolomics, and drug
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their performance evaluated in terms of classification accuracy, computational speed, and overall usability. Required knowledge Deep learning (CNNs, Transformers) and computer vision Knowledge distillation for model
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variability, and real-time monitoring requirements, with applications in manufacturing, healthcare, and service industries. The ultimate goal is to enhance process stability, reduce variability, and improve
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maximise efficiency. This project considers a future transport system that combines flying drones with conventional ground-level trucks. In this system, as a truck approaches a customer, a drone is launched
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. The goal is to find common brain mechanisms and networks that are effected by different kinds anaesthetics to see if this points to a 'backbone' for the generation of consciousness. Required knowledge
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hospital or population often fail when applied elsewhere due to distributional shifts. Since acquiring new labeled data is often costly or infeasible due to rare diseases, limited expert availability, and