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Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social
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are computationally expensive for modern large models. Incomplete Uncertainty Modeling: Most methods focus on single-modal data and fail to account for uncertainty arising from multi-view or multimodal interactions
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This project concerns the investigation of suitable socio-technical data infrastructure for law-enforcement research and development. International collaboration between law-enforcement agencies
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creative ambition, ensuring programs are supported by high-performing teams, integrated digital platforms, trusted data, and streamlined processes, positioning Monash to deliver impactful campaign outcomes
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embedding future-ready, data-led, customer-first ways of working. This role offers the rare chance to shape both strategy and culture, crafting the change narrative that aligns teams, accelerates adoption
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In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
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In the big-data era, the proliferation of data and the widespread adoption of data analytics have made data literacy a requisite skill for all professions, not just specialist data scientists
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& Communication Support: research materials in alternative formats (large print, Braille, audio); interpreters; written communication aids; speech-generating devices. Adaptive/Specialised Technology, Devices and
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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much
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autism [4]. For example, to measure anxiety, researchers may place a rodent in a large tub, record a top-down video and measure the time spent near the safety of walls [2]. These videos also contain rich